Annotation of imach/src/imach.c, revision 1.354
1.354 ! brouard 1: /* $Id: imach.c,v 1.353 2023/05/08 18:48:22 brouard Exp $
1.126 brouard 2: $State: Exp $
1.163 brouard 3: $Log: imach.c,v $
1.354 ! brouard 4: Revision 1.353 2023/05/08 18:48:22 brouard
! 5: *** empty log message ***
! 6:
1.353 brouard 7: Revision 1.352 2023/04/29 10:46:21 brouard
8: *** empty log message ***
9:
1.352 brouard 10: Revision 1.351 2023/04/29 10:43:47 brouard
11: Summary: 099r45
12:
1.351 brouard 13: Revision 1.350 2023/04/24 11:38:06 brouard
14: *** empty log message ***
15:
1.350 brouard 16: Revision 1.349 2023/01/31 09:19:37 brouard
17: Summary: Improvements in models with age*Vn*Vm
18:
1.348 brouard 19: Revision 1.347 2022/09/18 14:36:44 brouard
20: Summary: version 0.99r42
21:
1.347 brouard 22: Revision 1.346 2022/09/16 13:52:36 brouard
23: * src/imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
24:
1.346 brouard 25: Revision 1.345 2022/09/16 13:40:11 brouard
26: Summary: Version 0.99r41
27:
28: * imach.c (Module): 0.99r41 Was an error when product of timevarying and fixed. Using FixedV[of name] now. Thank you Feinuo
29:
1.345 brouard 30: Revision 1.344 2022/09/14 19:33:30 brouard
31: Summary: version 0.99r40
32:
33: * imach.c (Module): Fixing names of variables in T_ (thanks to Feinuo)
34:
1.344 brouard 35: Revision 1.343 2022/09/14 14:22:16 brouard
36: Summary: version 0.99r39
37:
38: * imach.c (Module): Version 0.99r39 with colored dummy covariates
39: (fixed or time varying), using new last columns of
40: ILK_parameter.txt file.
41:
1.343 brouard 42: Revision 1.342 2022/09/11 19:54:09 brouard
43: Summary: 0.99r38
44:
45: * imach.c (Module): Adding timevarying products of any kinds,
46: should work before shifting cotvar from ncovcol+nqv columns in
47: order to have a correspondance between the column of cotvar and
48: the id of column.
49: (Module): Some cleaning and adding covariates in ILK.txt
50:
1.342 brouard 51: Revision 1.341 2022/09/11 07:58:42 brouard
52: Summary: Version 0.99r38
53:
54: After adding change in cotvar.
55:
1.341 brouard 56: Revision 1.340 2022/09/11 07:53:11 brouard
57: Summary: Version imach 0.99r37
58:
59: * imach.c (Module): Adding timevarying products of any kinds,
60: should work before shifting cotvar from ncovcol+nqv columns in
61: order to have a correspondance between the column of cotvar and
62: the id of column.
63:
1.340 brouard 64: Revision 1.339 2022/09/09 17:55:22 brouard
65: Summary: version 0.99r37
66:
67: * imach.c (Module): Many improvements for fixing products of fixed
68: timevarying as well as fixed * fixed, and test with quantitative
69: covariate.
70:
1.339 brouard 71: Revision 1.338 2022/09/04 17:40:33 brouard
72: Summary: 0.99r36
73:
74: * imach.c (Module): Now the easy runs i.e. without result or
75: model=1+age only did not work. The defautl combination should be 1
76: and not 0 because everything hasn't been tranformed yet.
77:
1.338 brouard 78: Revision 1.337 2022/09/02 14:26:02 brouard
79: Summary: version 0.99r35
80:
81: * src/imach.c: Version 0.99r35 because it outputs same results with
82: 1+age+V1+V1*age for females and 1+age for females only
83: (education=1 noweight)
84:
1.337 brouard 85: Revision 1.336 2022/08/31 09:52:36 brouard
86: *** empty log message ***
87:
1.336 brouard 88: Revision 1.335 2022/08/31 08:23:16 brouard
89: Summary: improvements...
90:
1.335 brouard 91: Revision 1.334 2022/08/25 09:08:41 brouard
92: Summary: In progress for quantitative
93:
1.334 brouard 94: Revision 1.333 2022/08/21 09:10:30 brouard
95: * src/imach.c (Module): Version 0.99r33 A lot of changes in
96: reassigning covariates: my first idea was that people will always
97: use the first covariate V1 into the model but in fact they are
98: producing data with many covariates and can use an equation model
99: with some of the covariate; it means that in a model V2+V3 instead
100: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
101: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
102: the equation model is restricted to two variables only (V2, V3)
103: and the combination for V2 should be codtabm(k,1) instead of
104: (codtabm(k,2), and the code should be
105: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
106: made. All of these should be simplified once a day like we did in
107: hpxij() for example by using precov[nres] which is computed in
108: decoderesult for each nres of each resultline. Loop should be done
109: on the equation model globally by distinguishing only product with
110: age (which are changing with age) and no more on type of
111: covariates, single dummies, single covariates.
112:
1.333 brouard 113: Revision 1.332 2022/08/21 09:06:25 brouard
114: Summary: Version 0.99r33
115:
116: * src/imach.c (Module): Version 0.99r33 A lot of changes in
117: reassigning covariates: my first idea was that people will always
118: use the first covariate V1 into the model but in fact they are
119: producing data with many covariates and can use an equation model
120: with some of the covariate; it means that in a model V2+V3 instead
121: of codtabm(k,Tvaraff[j]) which calculates for combination k, for
122: three covariates (V1, V2, V3) the value of Tvaraff[j], but in fact
123: the equation model is restricted to two variables only (V2, V3)
124: and the combination for V2 should be codtabm(k,1) instead of
125: (codtabm(k,2), and the code should be
126: codtabm(k,TnsdVar[Tvaraff[j]]. Many many changes have been
127: made. All of these should be simplified once a day like we did in
128: hpxij() for example by using precov[nres] which is computed in
129: decoderesult for each nres of each resultline. Loop should be done
130: on the equation model globally by distinguishing only product with
131: age (which are changing with age) and no more on type of
132: covariates, single dummies, single covariates.
133:
1.332 brouard 134: Revision 1.331 2022/08/07 05:40:09 brouard
135: *** empty log message ***
136:
1.331 brouard 137: Revision 1.330 2022/08/06 07:18:25 brouard
138: Summary: last 0.99r31
139:
140: * imach.c (Module): Version of imach using partly decoderesult to rebuild xpxij function
141:
1.330 brouard 142: Revision 1.329 2022/08/03 17:29:54 brouard
143: * imach.c (Module): Many errors in graphs fixed with Vn*age covariates.
144:
1.329 brouard 145: Revision 1.328 2022/07/27 17:40:48 brouard
146: Summary: valgrind bug fixed by initializing to zero DummyV as well as Tage
147:
1.328 brouard 148: Revision 1.327 2022/07/27 14:47:35 brouard
149: Summary: Still a problem for one-step probabilities in case of quantitative variables
150:
1.327 brouard 151: Revision 1.326 2022/07/26 17:33:55 brouard
152: Summary: some test with nres=1
153:
1.326 brouard 154: Revision 1.325 2022/07/25 14:27:23 brouard
155: Summary: r30
156:
157: * imach.c (Module): Error cptcovn instead of nsd in bmij (was
158: coredumped, revealed by Feiuno, thank you.
159:
1.325 brouard 160: Revision 1.324 2022/07/23 17:44:26 brouard
161: *** empty log message ***
162:
1.324 brouard 163: Revision 1.323 2022/07/22 12:30:08 brouard
164: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
165:
1.323 brouard 166: Revision 1.322 2022/07/22 12:27:48 brouard
167: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
168:
1.322 brouard 169: Revision 1.321 2022/07/22 12:04:24 brouard
170: Summary: r28
171:
172: * imach.c (Module): Output of Wald test in the htm file and not only in the log.
173:
1.321 brouard 174: Revision 1.320 2022/06/02 05:10:11 brouard
175: *** empty log message ***
176:
1.320 brouard 177: Revision 1.319 2022/06/02 04:45:11 brouard
178: * imach.c (Module): Adding the Wald tests from the log to the main
179: htm for better display of the maximum likelihood estimators.
180:
1.319 brouard 181: Revision 1.318 2022/05/24 08:10:59 brouard
182: * imach.c (Module): Some attempts to find a bug of wrong estimates
183: of confidencce intervals with product in the equation modelC
184:
1.318 brouard 185: Revision 1.317 2022/05/15 15:06:23 brouard
186: * imach.c (Module): Some minor improvements
187:
1.317 brouard 188: Revision 1.316 2022/05/11 15:11:31 brouard
189: Summary: r27
190:
1.316 brouard 191: Revision 1.315 2022/05/11 15:06:32 brouard
192: *** empty log message ***
193:
1.315 brouard 194: Revision 1.314 2022/04/13 17:43:09 brouard
195: * imach.c (Module): Adding link to text data files
196:
1.314 brouard 197: Revision 1.313 2022/04/11 15:57:42 brouard
198: * imach.c (Module): Error in rewriting the 'r' file with yearsfproj or yearsbproj fixed
199:
1.313 brouard 200: Revision 1.312 2022/04/05 21:24:39 brouard
201: *** empty log message ***
202:
1.312 brouard 203: Revision 1.311 2022/04/05 21:03:51 brouard
204: Summary: Fixed quantitative covariates
205:
206: Fixed covariates (dummy or quantitative)
207: with missing values have never been allowed but are ERRORS and
208: program quits. Standard deviations of fixed covariates were
209: wrongly computed. Mean and standard deviations of time varying
210: covariates are still not computed.
211:
1.311 brouard 212: Revision 1.310 2022/03/17 08:45:53 brouard
213: Summary: 99r25
214:
215: Improving detection of errors: result lines should be compatible with
216: the model.
217:
1.310 brouard 218: Revision 1.309 2021/05/20 12:39:14 brouard
219: Summary: Version 0.99r24
220:
1.309 brouard 221: Revision 1.308 2021/03/31 13:11:57 brouard
222: Summary: Version 0.99r23
223:
224:
225: * imach.c (Module): Still bugs in the result loop. Thank to Holly Benett
226:
1.308 brouard 227: Revision 1.307 2021/03/08 18:11:32 brouard
228: Summary: 0.99r22 fixed bug on result:
229:
1.307 brouard 230: Revision 1.306 2021/02/20 15:44:02 brouard
231: Summary: Version 0.99r21
232:
233: * imach.c (Module): Fix bug on quitting after result lines!
234: (Module): Version 0.99r21
235:
1.306 brouard 236: Revision 1.305 2021/02/20 15:28:30 brouard
237: * imach.c (Module): Fix bug on quitting after result lines!
238:
1.305 brouard 239: Revision 1.304 2021/02/12 11:34:20 brouard
240: * imach.c (Module): The use of a Windows BOM (huge) file is now an error
241:
1.304 brouard 242: Revision 1.303 2021/02/11 19:50:15 brouard
243: * (Module): imach.c Someone entered 'results:' instead of 'result:'. Now it is an error which is printed.
244:
1.303 brouard 245: Revision 1.302 2020/02/22 21:00:05 brouard
246: * (Module): imach.c Update mle=-3 (for computing Life expectancy
247: and life table from the data without any state)
248:
1.302 brouard 249: Revision 1.301 2019/06/04 13:51:20 brouard
250: Summary: Error in 'r'parameter file backcast yearsbproj instead of yearsfproj
251:
1.301 brouard 252: Revision 1.300 2019/05/22 19:09:45 brouard
253: Summary: version 0.99r19 of May 2019
254:
1.300 brouard 255: Revision 1.299 2019/05/22 18:37:08 brouard
256: Summary: Cleaned 0.99r19
257:
1.299 brouard 258: Revision 1.298 2019/05/22 18:19:56 brouard
259: *** empty log message ***
260:
1.298 brouard 261: Revision 1.297 2019/05/22 17:56:10 brouard
262: Summary: Fix bug by moving date2dmy and nhstepm which gaefin=-1
263:
1.297 brouard 264: Revision 1.296 2019/05/20 13:03:18 brouard
265: Summary: Projection syntax simplified
266:
267:
268: We can now start projections, forward or backward, from the mean date
269: of inteviews up to or down to a number of years of projection:
270: prevforecast=1 yearsfproj=15.3 mobil_average=0
271: or
272: prevforecast=1 starting-proj-date=1/1/2007 final-proj-date=12/31/2017 mobil_average=0
273: or
274: prevbackcast=1 yearsbproj=12.3 mobil_average=1
275: or
276: prevbackcast=1 starting-back-date=1/10/1999 final-back-date=1/1/1985 mobil_average=1
277:
1.296 brouard 278: Revision 1.295 2019/05/18 09:52:50 brouard
279: Summary: doxygen tex bug
280:
1.295 brouard 281: Revision 1.294 2019/05/16 14:54:33 brouard
282: Summary: There was some wrong lines added
283:
1.294 brouard 284: Revision 1.293 2019/05/09 15:17:34 brouard
285: *** empty log message ***
286:
1.293 brouard 287: Revision 1.292 2019/05/09 14:17:20 brouard
288: Summary: Some updates
289:
1.292 brouard 290: Revision 1.291 2019/05/09 13:44:18 brouard
291: Summary: Before ncovmax
292:
1.291 brouard 293: Revision 1.290 2019/05/09 13:39:37 brouard
294: Summary: 0.99r18 unlimited number of individuals
295:
296: The number n which was limited to 20,000 cases is now unlimited, from firstobs to lastobs. If the number is too for the virtual memory, probably an error will occur.
297:
1.290 brouard 298: Revision 1.289 2018/12/13 09:16:26 brouard
299: Summary: Bug for young ages (<-30) will be in r17
300:
1.289 brouard 301: Revision 1.288 2018/05/02 20:58:27 brouard
302: Summary: Some bugs fixed
303:
1.288 brouard 304: Revision 1.287 2018/05/01 17:57:25 brouard
305: Summary: Bug fixed by providing frequencies only for non missing covariates
306:
1.287 brouard 307: Revision 1.286 2018/04/27 14:27:04 brouard
308: Summary: some minor bugs
309:
1.286 brouard 310: Revision 1.285 2018/04/21 21:02:16 brouard
311: Summary: Some bugs fixed, valgrind tested
312:
1.285 brouard 313: Revision 1.284 2018/04/20 05:22:13 brouard
314: Summary: Computing mean and stdeviation of fixed quantitative variables
315:
1.284 brouard 316: Revision 1.283 2018/04/19 14:49:16 brouard
317: Summary: Some minor bugs fixed
318:
1.283 brouard 319: Revision 1.282 2018/02/27 22:50:02 brouard
320: *** empty log message ***
321:
1.282 brouard 322: Revision 1.281 2018/02/27 19:25:23 brouard
323: Summary: Adding second argument for quitting
324:
1.281 brouard 325: Revision 1.280 2018/02/21 07:58:13 brouard
326: Summary: 0.99r15
327:
328: New Makefile with recent VirtualBox 5.26. Bug in sqrt negatve in imach.c
329:
1.280 brouard 330: Revision 1.279 2017/07/20 13:35:01 brouard
331: Summary: temporary working
332:
1.279 brouard 333: Revision 1.278 2017/07/19 14:09:02 brouard
334: Summary: Bug for mobil_average=0 and prevforecast fixed(?)
335:
1.278 brouard 336: Revision 1.277 2017/07/17 08:53:49 brouard
337: Summary: BOM files can be read now
338:
1.277 brouard 339: Revision 1.276 2017/06/30 15:48:31 brouard
340: Summary: Graphs improvements
341:
1.276 brouard 342: Revision 1.275 2017/06/30 13:39:33 brouard
343: Summary: Saito's color
344:
1.275 brouard 345: Revision 1.274 2017/06/29 09:47:08 brouard
346: Summary: Version 0.99r14
347:
1.274 brouard 348: Revision 1.273 2017/06/27 11:06:02 brouard
349: Summary: More documentation on projections
350:
1.273 brouard 351: Revision 1.272 2017/06/27 10:22:40 brouard
352: Summary: Color of backprojection changed from 6 to 5(yellow)
353:
1.272 brouard 354: Revision 1.271 2017/06/27 10:17:50 brouard
355: Summary: Some bug with rint
356:
1.271 brouard 357: Revision 1.270 2017/05/24 05:45:29 brouard
358: *** empty log message ***
359:
1.270 brouard 360: Revision 1.269 2017/05/23 08:39:25 brouard
361: Summary: Code into subroutine, cleanings
362:
1.269 brouard 363: Revision 1.268 2017/05/18 20:09:32 brouard
364: Summary: backprojection and confidence intervals of backprevalence
365:
1.268 brouard 366: Revision 1.267 2017/05/13 10:25:05 brouard
367: Summary: temporary save for backprojection
368:
1.267 brouard 369: Revision 1.266 2017/05/13 07:26:12 brouard
370: Summary: Version 0.99r13 (improvements and bugs fixed)
371:
1.266 brouard 372: Revision 1.265 2017/04/26 16:22:11 brouard
373: Summary: imach 0.99r13 Some bugs fixed
374:
1.265 brouard 375: Revision 1.264 2017/04/26 06:01:29 brouard
376: Summary: Labels in graphs
377:
1.264 brouard 378: Revision 1.263 2017/04/24 15:23:15 brouard
379: Summary: to save
380:
1.263 brouard 381: Revision 1.262 2017/04/18 16:48:12 brouard
382: *** empty log message ***
383:
1.262 brouard 384: Revision 1.261 2017/04/05 10:14:09 brouard
385: Summary: Bug in E_ as well as in T_ fixed nres-1 vs k1-1
386:
1.261 brouard 387: Revision 1.260 2017/04/04 17:46:59 brouard
388: Summary: Gnuplot indexations fixed (humm)
389:
1.260 brouard 390: Revision 1.259 2017/04/04 13:01:16 brouard
391: Summary: Some errors to warnings only if date of death is unknown but status is death we could set to pi3
392:
1.259 brouard 393: Revision 1.258 2017/04/03 10:17:47 brouard
394: Summary: Version 0.99r12
395:
396: Some cleanings, conformed with updated documentation.
397:
1.258 brouard 398: Revision 1.257 2017/03/29 16:53:30 brouard
399: Summary: Temp
400:
1.257 brouard 401: Revision 1.256 2017/03/27 05:50:23 brouard
402: Summary: Temporary
403:
1.256 brouard 404: Revision 1.255 2017/03/08 16:02:28 brouard
405: Summary: IMaCh version 0.99r10 bugs in gnuplot fixed
406:
1.255 brouard 407: Revision 1.254 2017/03/08 07:13:00 brouard
408: Summary: Fixing data parameter line
409:
1.254 brouard 410: Revision 1.253 2016/12/15 11:59:41 brouard
411: Summary: 0.99 in progress
412:
1.253 brouard 413: Revision 1.252 2016/09/15 21:15:37 brouard
414: *** empty log message ***
415:
1.252 brouard 416: Revision 1.251 2016/09/15 15:01:13 brouard
417: Summary: not working
418:
1.251 brouard 419: Revision 1.250 2016/09/08 16:07:27 brouard
420: Summary: continue
421:
1.250 brouard 422: Revision 1.249 2016/09/07 17:14:18 brouard
423: Summary: Starting values from frequencies
424:
1.249 brouard 425: Revision 1.248 2016/09/07 14:10:18 brouard
426: *** empty log message ***
427:
1.248 brouard 428: Revision 1.247 2016/09/02 11:11:21 brouard
429: *** empty log message ***
430:
1.247 brouard 431: Revision 1.246 2016/09/02 08:49:22 brouard
432: *** empty log message ***
433:
1.246 brouard 434: Revision 1.245 2016/09/02 07:25:01 brouard
435: *** empty log message ***
436:
1.245 brouard 437: Revision 1.244 2016/09/02 07:17:34 brouard
438: *** empty log message ***
439:
1.244 brouard 440: Revision 1.243 2016/09/02 06:45:35 brouard
441: *** empty log message ***
442:
1.243 brouard 443: Revision 1.242 2016/08/30 15:01:20 brouard
444: Summary: Fixing a lots
445:
1.242 brouard 446: Revision 1.241 2016/08/29 17:17:25 brouard
447: Summary: gnuplot problem in Back projection to fix
448:
1.241 brouard 449: Revision 1.240 2016/08/29 07:53:18 brouard
450: Summary: Better
451:
1.240 brouard 452: Revision 1.239 2016/08/26 15:51:03 brouard
453: Summary: Improvement in Powell output in order to copy and paste
454:
455: Author:
456:
1.239 brouard 457: Revision 1.238 2016/08/26 14:23:35 brouard
458: Summary: Starting tests of 0.99
459:
1.238 brouard 460: Revision 1.237 2016/08/26 09:20:19 brouard
461: Summary: to valgrind
462:
1.237 brouard 463: Revision 1.236 2016/08/25 10:50:18 brouard
464: *** empty log message ***
465:
1.236 brouard 466: Revision 1.235 2016/08/25 06:59:23 brouard
467: *** empty log message ***
468:
1.235 brouard 469: Revision 1.234 2016/08/23 16:51:20 brouard
470: *** empty log message ***
471:
1.234 brouard 472: Revision 1.233 2016/08/23 07:40:50 brouard
473: Summary: not working
474:
1.233 brouard 475: Revision 1.232 2016/08/22 14:20:21 brouard
476: Summary: not working
477:
1.232 brouard 478: Revision 1.231 2016/08/22 07:17:15 brouard
479: Summary: not working
480:
1.231 brouard 481: Revision 1.230 2016/08/22 06:55:53 brouard
482: Summary: Not working
483:
1.230 brouard 484: Revision 1.229 2016/07/23 09:45:53 brouard
485: Summary: Completing for func too
486:
1.229 brouard 487: Revision 1.228 2016/07/22 17:45:30 brouard
488: Summary: Fixing some arrays, still debugging
489:
1.227 brouard 490: Revision 1.226 2016/07/12 18:42:34 brouard
491: Summary: temp
492:
1.226 brouard 493: Revision 1.225 2016/07/12 08:40:03 brouard
494: Summary: saving but not running
495:
1.225 brouard 496: Revision 1.224 2016/07/01 13:16:01 brouard
497: Summary: Fixes
498:
1.224 brouard 499: Revision 1.223 2016/02/19 09:23:35 brouard
500: Summary: temporary
501:
1.223 brouard 502: Revision 1.222 2016/02/17 08:14:50 brouard
503: Summary: Probably last 0.98 stable version 0.98r6
504:
1.222 brouard 505: Revision 1.221 2016/02/15 23:35:36 brouard
506: Summary: minor bug
507:
1.220 brouard 508: Revision 1.219 2016/02/15 00:48:12 brouard
509: *** empty log message ***
510:
1.219 brouard 511: Revision 1.218 2016/02/12 11:29:23 brouard
512: Summary: 0.99 Back projections
513:
1.218 brouard 514: Revision 1.217 2015/12/23 17:18:31 brouard
515: Summary: Experimental backcast
516:
1.217 brouard 517: Revision 1.216 2015/12/18 17:32:11 brouard
518: Summary: 0.98r4 Warning and status=-2
519:
520: Version 0.98r4 is now:
521: - displaying an error when status is -1, date of interview unknown and date of death known;
522: - permitting a status -2 when the vital status is unknown at a known date of right truncation.
523: Older changes concerning s=-2, dating from 2005 have been supersed.
524:
1.216 brouard 525: Revision 1.215 2015/12/16 08:52:24 brouard
526: Summary: 0.98r4 working
527:
1.215 brouard 528: Revision 1.214 2015/12/16 06:57:54 brouard
529: Summary: temporary not working
530:
1.214 brouard 531: Revision 1.213 2015/12/11 18:22:17 brouard
532: Summary: 0.98r4
533:
1.213 brouard 534: Revision 1.212 2015/11/21 12:47:24 brouard
535: Summary: minor typo
536:
1.212 brouard 537: Revision 1.211 2015/11/21 12:41:11 brouard
538: Summary: 0.98r3 with some graph of projected cross-sectional
539:
540: Author: Nicolas Brouard
541:
1.211 brouard 542: Revision 1.210 2015/11/18 17:41:20 brouard
1.252 brouard 543: Summary: Start working on projected prevalences Revision 1.209 2015/11/17 22:12:03 brouard
1.210 brouard 544: Summary: Adding ftolpl parameter
545: Author: N Brouard
546:
547: We had difficulties to get smoothed confidence intervals. It was due
548: to the period prevalence which wasn't computed accurately. The inner
549: parameter ftolpl is now an outer parameter of the .imach parameter
550: file after estepm. If ftolpl is small 1.e-4 and estepm too,
551: computation are long.
552:
1.209 brouard 553: Revision 1.208 2015/11/17 14:31:57 brouard
554: Summary: temporary
555:
1.208 brouard 556: Revision 1.207 2015/10/27 17:36:57 brouard
557: *** empty log message ***
558:
1.207 brouard 559: Revision 1.206 2015/10/24 07:14:11 brouard
560: *** empty log message ***
561:
1.206 brouard 562: Revision 1.205 2015/10/23 15:50:53 brouard
563: Summary: 0.98r3 some clarification for graphs on likelihood contributions
564:
1.205 brouard 565: Revision 1.204 2015/10/01 16:20:26 brouard
566: Summary: Some new graphs of contribution to likelihood
567:
1.204 brouard 568: Revision 1.203 2015/09/30 17:45:14 brouard
569: Summary: looking at better estimation of the hessian
570:
571: Also a better criteria for convergence to the period prevalence And
572: therefore adding the number of years needed to converge. (The
573: prevalence in any alive state shold sum to one
574:
1.203 brouard 575: Revision 1.202 2015/09/22 19:45:16 brouard
576: Summary: Adding some overall graph on contribution to likelihood. Might change
577:
1.202 brouard 578: Revision 1.201 2015/09/15 17:34:58 brouard
579: Summary: 0.98r0
580:
581: - Some new graphs like suvival functions
582: - Some bugs fixed like model=1+age+V2.
583:
1.201 brouard 584: Revision 1.200 2015/09/09 16:53:55 brouard
585: Summary: Big bug thanks to Flavia
586:
587: Even model=1+age+V2. did not work anymore
588:
1.200 brouard 589: Revision 1.199 2015/09/07 14:09:23 brouard
590: Summary: 0.98q6 changing default small png format for graph to vectorized svg.
591:
1.199 brouard 592: Revision 1.198 2015/09/03 07:14:39 brouard
593: Summary: 0.98q5 Flavia
594:
1.198 brouard 595: Revision 1.197 2015/09/01 18:24:39 brouard
596: *** empty log message ***
597:
1.197 brouard 598: Revision 1.196 2015/08/18 23:17:52 brouard
599: Summary: 0.98q5
600:
1.196 brouard 601: Revision 1.195 2015/08/18 16:28:39 brouard
602: Summary: Adding a hack for testing purpose
603:
604: After reading the title, ftol and model lines, if the comment line has
605: a q, starting with #q, the answer at the end of the run is quit. It
606: permits to run test files in batch with ctest. The former workaround was
607: $ echo q | imach foo.imach
608:
1.195 brouard 609: Revision 1.194 2015/08/18 13:32:00 brouard
610: Summary: Adding error when the covariance matrix doesn't contain the exact number of lines required by the model line.
611:
1.194 brouard 612: Revision 1.193 2015/08/04 07:17:42 brouard
613: Summary: 0.98q4
614:
1.193 brouard 615: Revision 1.192 2015/07/16 16:49:02 brouard
616: Summary: Fixing some outputs
617:
1.192 brouard 618: Revision 1.191 2015/07/14 10:00:33 brouard
619: Summary: Some fixes
620:
1.191 brouard 621: Revision 1.190 2015/05/05 08:51:13 brouard
622: Summary: Adding digits in output parameters (7 digits instead of 6)
623:
624: Fix 1+age+.
625:
1.190 brouard 626: Revision 1.189 2015/04/30 14:45:16 brouard
627: Summary: 0.98q2
628:
1.189 brouard 629: Revision 1.188 2015/04/30 08:27:53 brouard
630: *** empty log message ***
631:
1.188 brouard 632: Revision 1.187 2015/04/29 09:11:15 brouard
633: *** empty log message ***
634:
1.187 brouard 635: Revision 1.186 2015/04/23 12:01:52 brouard
636: Summary: V1*age is working now, version 0.98q1
637:
638: Some codes had been disabled in order to simplify and Vn*age was
639: working in the optimization phase, ie, giving correct MLE parameters,
640: but, as usual, outputs were not correct and program core dumped.
641:
1.186 brouard 642: Revision 1.185 2015/03/11 13:26:42 brouard
643: Summary: Inclusion of compile and links command line for Intel Compiler
644:
1.185 brouard 645: Revision 1.184 2015/03/11 11:52:39 brouard
646: Summary: Back from Windows 8. Intel Compiler
647:
1.184 brouard 648: Revision 1.183 2015/03/10 20:34:32 brouard
649: Summary: 0.98q0, trying with directest, mnbrak fixed
650:
651: We use directest instead of original Powell test; probably no
652: incidence on the results, but better justifications;
653: We fixed Numerical Recipes mnbrak routine which was wrong and gave
654: wrong results.
655:
1.183 brouard 656: Revision 1.182 2015/02/12 08:19:57 brouard
657: Summary: Trying to keep directest which seems simpler and more general
658: Author: Nicolas Brouard
659:
1.182 brouard 660: Revision 1.181 2015/02/11 23:22:24 brouard
661: Summary: Comments on Powell added
662:
663: Author:
664:
1.181 brouard 665: Revision 1.180 2015/02/11 17:33:45 brouard
666: Summary: Finishing move from main to function (hpijx and prevalence_limit)
667:
1.180 brouard 668: Revision 1.179 2015/01/04 09:57:06 brouard
669: Summary: back to OS/X
670:
1.179 brouard 671: Revision 1.178 2015/01/04 09:35:48 brouard
672: *** empty log message ***
673:
1.178 brouard 674: Revision 1.177 2015/01/03 18:40:56 brouard
675: Summary: Still testing ilc32 on OSX
676:
1.177 brouard 677: Revision 1.176 2015/01/03 16:45:04 brouard
678: *** empty log message ***
679:
1.176 brouard 680: Revision 1.175 2015/01/03 16:33:42 brouard
681: *** empty log message ***
682:
1.175 brouard 683: Revision 1.174 2015/01/03 16:15:49 brouard
684: Summary: Still in cross-compilation
685:
1.174 brouard 686: Revision 1.173 2015/01/03 12:06:26 brouard
687: Summary: trying to detect cross-compilation
688:
1.173 brouard 689: Revision 1.172 2014/12/27 12:07:47 brouard
690: Summary: Back from Visual Studio and Intel, options for compiling for Windows XP
691:
1.172 brouard 692: Revision 1.171 2014/12/23 13:26:59 brouard
693: Summary: Back from Visual C
694:
695: Still problem with utsname.h on Windows
696:
1.171 brouard 697: Revision 1.170 2014/12/23 11:17:12 brouard
698: Summary: Cleaning some \%% back to %%
699:
700: The escape was mandatory for a specific compiler (which one?), but too many warnings.
701:
1.170 brouard 702: Revision 1.169 2014/12/22 23:08:31 brouard
703: Summary: 0.98p
704:
705: Outputs some informations on compiler used, OS etc. Testing on different platforms.
706:
1.169 brouard 707: Revision 1.168 2014/12/22 15:17:42 brouard
1.170 brouard 708: Summary: update
1.169 brouard 709:
1.168 brouard 710: Revision 1.167 2014/12/22 13:50:56 brouard
711: Summary: Testing uname and compiler version and if compiled 32 or 64
712:
713: Testing on Linux 64
714:
1.167 brouard 715: Revision 1.166 2014/12/22 11:40:47 brouard
716: *** empty log message ***
717:
1.166 brouard 718: Revision 1.165 2014/12/16 11:20:36 brouard
719: Summary: After compiling on Visual C
720:
721: * imach.c (Module): Merging 1.61 to 1.162
722:
1.165 brouard 723: Revision 1.164 2014/12/16 10:52:11 brouard
724: Summary: Merging with Visual C after suppressing some warnings for unused variables. Also fixing Saito's bug 0.98Xn
725:
726: * imach.c (Module): Merging 1.61 to 1.162
727:
1.164 brouard 728: Revision 1.163 2014/12/16 10:30:11 brouard
729: * imach.c (Module): Merging 1.61 to 1.162
730:
1.163 brouard 731: Revision 1.162 2014/09/25 11:43:39 brouard
732: Summary: temporary backup 0.99!
733:
1.162 brouard 734: Revision 1.1 2014/09/16 11:06:58 brouard
735: Summary: With some code (wrong) for nlopt
736:
737: Author:
738:
739: Revision 1.161 2014/09/15 20:41:41 brouard
740: Summary: Problem with macro SQR on Intel compiler
741:
1.161 brouard 742: Revision 1.160 2014/09/02 09:24:05 brouard
743: *** empty log message ***
744:
1.160 brouard 745: Revision 1.159 2014/09/01 10:34:10 brouard
746: Summary: WIN32
747: Author: Brouard
748:
1.159 brouard 749: Revision 1.158 2014/08/27 17:11:51 brouard
750: *** empty log message ***
751:
1.158 brouard 752: Revision 1.157 2014/08/27 16:26:55 brouard
753: Summary: Preparing windows Visual studio version
754: Author: Brouard
755:
756: In order to compile on Visual studio, time.h is now correct and time_t
757: and tm struct should be used. difftime should be used but sometimes I
758: just make the differences in raw time format (time(&now).
759: Trying to suppress #ifdef LINUX
760: Add xdg-open for __linux in order to open default browser.
761:
1.157 brouard 762: Revision 1.156 2014/08/25 20:10:10 brouard
763: *** empty log message ***
764:
1.156 brouard 765: Revision 1.155 2014/08/25 18:32:34 brouard
766: Summary: New compile, minor changes
767: Author: Brouard
768:
1.155 brouard 769: Revision 1.154 2014/06/20 17:32:08 brouard
770: Summary: Outputs now all graphs of convergence to period prevalence
771:
1.154 brouard 772: Revision 1.153 2014/06/20 16:45:46 brouard
773: Summary: If 3 live state, convergence to period prevalence on same graph
774: Author: Brouard
775:
1.153 brouard 776: Revision 1.152 2014/06/18 17:54:09 brouard
777: Summary: open browser, use gnuplot on same dir than imach if not found in the path
778:
1.152 brouard 779: Revision 1.151 2014/06/18 16:43:30 brouard
780: *** empty log message ***
781:
1.151 brouard 782: Revision 1.150 2014/06/18 16:42:35 brouard
783: Summary: If gnuplot is not in the path try on same directory than imach binary (OSX)
784: Author: brouard
785:
1.150 brouard 786: Revision 1.149 2014/06/18 15:51:14 brouard
787: Summary: Some fixes in parameter files errors
788: Author: Nicolas Brouard
789:
1.149 brouard 790: Revision 1.148 2014/06/17 17:38:48 brouard
791: Summary: Nothing new
792: Author: Brouard
793:
794: Just a new packaging for OS/X version 0.98nS
795:
1.148 brouard 796: Revision 1.147 2014/06/16 10:33:11 brouard
797: *** empty log message ***
798:
1.147 brouard 799: Revision 1.146 2014/06/16 10:20:28 brouard
800: Summary: Merge
801: Author: Brouard
802:
803: Merge, before building revised version.
804:
1.146 brouard 805: Revision 1.145 2014/06/10 21:23:15 brouard
806: Summary: Debugging with valgrind
807: Author: Nicolas Brouard
808:
809: Lot of changes in order to output the results with some covariates
810: After the Edimburgh REVES conference 2014, it seems mandatory to
811: improve the code.
812: No more memory valgrind error but a lot has to be done in order to
813: continue the work of splitting the code into subroutines.
814: Also, decodemodel has been improved. Tricode is still not
815: optimal. nbcode should be improved. Documentation has been added in
816: the source code.
817:
1.144 brouard 818: Revision 1.143 2014/01/26 09:45:38 brouard
819: Summary: Version 0.98nR (to be improved, but gives same optimization results as 0.98k. Nice, promising
820:
821: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
822: (Module): Version 0.98nR Running ok, but output format still only works for three covariates.
823:
1.143 brouard 824: Revision 1.142 2014/01/26 03:57:36 brouard
825: Summary: gnuplot changed plot w l 1 has to be changed to plot w l lt 2
826:
827: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
828:
1.142 brouard 829: Revision 1.141 2014/01/26 02:42:01 brouard
830: * imach.c (Module): Trying to merge old staffs together while being at Tokyo. Not tested...
831:
1.141 brouard 832: Revision 1.140 2011/09/02 10:37:54 brouard
833: Summary: times.h is ok with mingw32 now.
834:
1.140 brouard 835: Revision 1.139 2010/06/14 07:50:17 brouard
836: After the theft of my laptop, I probably lost some lines of codes which were not uploaded to the CVS tree.
837: I remember having already fixed agemin agemax which are pointers now but not cvs saved.
838:
1.139 brouard 839: Revision 1.138 2010/04/30 18:19:40 brouard
840: *** empty log message ***
841:
1.138 brouard 842: Revision 1.137 2010/04/29 18:11:38 brouard
843: (Module): Checking covariates for more complex models
844: than V1+V2. A lot of change to be done. Unstable.
845:
1.137 brouard 846: Revision 1.136 2010/04/26 20:30:53 brouard
847: (Module): merging some libgsl code. Fixing computation
848: of likelione (using inter/intrapolation if mle = 0) in order to
849: get same likelihood as if mle=1.
850: Some cleaning of code and comments added.
851:
1.136 brouard 852: Revision 1.135 2009/10/29 15:33:14 brouard
853: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
854:
1.135 brouard 855: Revision 1.134 2009/10/29 13:18:53 brouard
856: (Module): Now imach stops if date of birth, at least year of birth, is not given. Some cleaning of the code.
857:
1.134 brouard 858: Revision 1.133 2009/07/06 10:21:25 brouard
859: just nforces
860:
1.133 brouard 861: Revision 1.132 2009/07/06 08:22:05 brouard
862: Many tings
863:
1.132 brouard 864: Revision 1.131 2009/06/20 16:22:47 brouard
865: Some dimensions resccaled
866:
1.131 brouard 867: Revision 1.130 2009/05/26 06:44:34 brouard
868: (Module): Max Covariate is now set to 20 instead of 8. A
869: lot of cleaning with variables initialized to 0. Trying to make
870: V2+V3*age+V1+V4 strb=V3*age+V1+V4 working better.
871:
1.130 brouard 872: Revision 1.129 2007/08/31 13:49:27 lievre
873: Modification of the way of exiting when the covariate is not binary in order to see on the window the error message before exiting
874:
1.129 lievre 875: Revision 1.128 2006/06/30 13:02:05 brouard
876: (Module): Clarifications on computing e.j
877:
1.128 brouard 878: Revision 1.127 2006/04/28 18:11:50 brouard
879: (Module): Yes the sum of survivors was wrong since
880: imach-114 because nhstepm was no more computed in the age
881: loop. Now we define nhstepma in the age loop.
882: (Module): In order to speed up (in case of numerous covariates) we
883: compute health expectancies (without variances) in a first step
884: and then all the health expectancies with variances or standard
885: deviation (needs data from the Hessian matrices) which slows the
886: computation.
887: In the future we should be able to stop the program is only health
888: expectancies and graph are needed without standard deviations.
889:
1.127 brouard 890: Revision 1.126 2006/04/28 17:23:28 brouard
891: (Module): Yes the sum of survivors was wrong since
892: imach-114 because nhstepm was no more computed in the age
893: loop. Now we define nhstepma in the age loop.
894: Version 0.98h
895:
1.126 brouard 896: Revision 1.125 2006/04/04 15:20:31 lievre
897: Errors in calculation of health expectancies. Age was not initialized.
898: Forecasting file added.
899:
900: Revision 1.124 2006/03/22 17:13:53 lievre
901: Parameters are printed with %lf instead of %f (more numbers after the comma).
902: The log-likelihood is printed in the log file
903:
904: Revision 1.123 2006/03/20 10:52:43 brouard
905: * imach.c (Module): <title> changed, corresponds to .htm file
906: name. <head> headers where missing.
907:
908: * imach.c (Module): Weights can have a decimal point as for
909: English (a comma might work with a correct LC_NUMERIC environment,
910: otherwise the weight is truncated).
911: Modification of warning when the covariates values are not 0 or
912: 1.
913: Version 0.98g
914:
915: Revision 1.122 2006/03/20 09:45:41 brouard
916: (Module): Weights can have a decimal point as for
917: English (a comma might work with a correct LC_NUMERIC environment,
918: otherwise the weight is truncated).
919: Modification of warning when the covariates values are not 0 or
920: 1.
921: Version 0.98g
922:
923: Revision 1.121 2006/03/16 17:45:01 lievre
924: * imach.c (Module): Comments concerning covariates added
925:
926: * imach.c (Module): refinements in the computation of lli if
927: status=-2 in order to have more reliable computation if stepm is
928: not 1 month. Version 0.98f
929:
930: Revision 1.120 2006/03/16 15:10:38 lievre
931: (Module): refinements in the computation of lli if
932: status=-2 in order to have more reliable computation if stepm is
933: not 1 month. Version 0.98f
934:
935: Revision 1.119 2006/03/15 17:42:26 brouard
936: (Module): Bug if status = -2, the loglikelihood was
937: computed as likelihood omitting the logarithm. Version O.98e
938:
939: Revision 1.118 2006/03/14 18:20:07 brouard
940: (Module): varevsij Comments added explaining the second
941: table of variances if popbased=1 .
942: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
943: (Module): Function pstamp added
944: (Module): Version 0.98d
945:
946: Revision 1.117 2006/03/14 17:16:22 brouard
947: (Module): varevsij Comments added explaining the second
948: table of variances if popbased=1 .
949: (Module): Covariances of eij, ekl added, graphs fixed, new html link.
950: (Module): Function pstamp added
951: (Module): Version 0.98d
952:
953: Revision 1.116 2006/03/06 10:29:27 brouard
954: (Module): Variance-covariance wrong links and
955: varian-covariance of ej. is needed (Saito).
956:
957: Revision 1.115 2006/02/27 12:17:45 brouard
958: (Module): One freematrix added in mlikeli! 0.98c
959:
960: Revision 1.114 2006/02/26 12:57:58 brouard
961: (Module): Some improvements in processing parameter
962: filename with strsep.
963:
964: Revision 1.113 2006/02/24 14:20:24 brouard
965: (Module): Memory leaks checks with valgrind and:
966: datafile was not closed, some imatrix were not freed and on matrix
967: allocation too.
968:
969: Revision 1.112 2006/01/30 09:55:26 brouard
970: (Module): Back to gnuplot.exe instead of wgnuplot.exe
971:
972: Revision 1.111 2006/01/25 20:38:18 brouard
973: (Module): Lots of cleaning and bugs added (Gompertz)
974: (Module): Comments can be added in data file. Missing date values
975: can be a simple dot '.'.
976:
977: Revision 1.110 2006/01/25 00:51:50 brouard
978: (Module): Lots of cleaning and bugs added (Gompertz)
979:
980: Revision 1.109 2006/01/24 19:37:15 brouard
981: (Module): Comments (lines starting with a #) are allowed in data.
982:
983: Revision 1.108 2006/01/19 18:05:42 lievre
984: Gnuplot problem appeared...
985: To be fixed
986:
987: Revision 1.107 2006/01/19 16:20:37 brouard
988: Test existence of gnuplot in imach path
989:
990: Revision 1.106 2006/01/19 13:24:36 brouard
991: Some cleaning and links added in html output
992:
993: Revision 1.105 2006/01/05 20:23:19 lievre
994: *** empty log message ***
995:
996: Revision 1.104 2005/09/30 16:11:43 lievre
997: (Module): sump fixed, loop imx fixed, and simplifications.
998: (Module): If the status is missing at the last wave but we know
999: that the person is alive, then we can code his/her status as -2
1000: (instead of missing=-1 in earlier versions) and his/her
1001: contributions to the likelihood is 1 - Prob of dying from last
1002: health status (= 1-p13= p11+p12 in the easiest case of somebody in
1003: the healthy state at last known wave). Version is 0.98
1004:
1005: Revision 1.103 2005/09/30 15:54:49 lievre
1006: (Module): sump fixed, loop imx fixed, and simplifications.
1007:
1008: Revision 1.102 2004/09/15 17:31:30 brouard
1009: Add the possibility to read data file including tab characters.
1010:
1011: Revision 1.101 2004/09/15 10:38:38 brouard
1012: Fix on curr_time
1013:
1014: Revision 1.100 2004/07/12 18:29:06 brouard
1015: Add version for Mac OS X. Just define UNIX in Makefile
1016:
1017: Revision 1.99 2004/06/05 08:57:40 brouard
1018: *** empty log message ***
1019:
1020: Revision 1.98 2004/05/16 15:05:56 brouard
1021: New version 0.97 . First attempt to estimate force of mortality
1022: directly from the data i.e. without the need of knowing the health
1023: state at each age, but using a Gompertz model: log u =a + b*age .
1024: This is the basic analysis of mortality and should be done before any
1025: other analysis, in order to test if the mortality estimated from the
1026: cross-longitudinal survey is different from the mortality estimated
1027: from other sources like vital statistic data.
1028:
1029: The same imach parameter file can be used but the option for mle should be -3.
1030:
1.324 brouard 1031: Agnès, who wrote this part of the code, tried to keep most of the
1.126 brouard 1032: former routines in order to include the new code within the former code.
1033:
1034: The output is very simple: only an estimate of the intercept and of
1035: the slope with 95% confident intervals.
1036:
1037: Current limitations:
1038: A) Even if you enter covariates, i.e. with the
1039: model= V1+V2 equation for example, the programm does only estimate a unique global model without covariates.
1040: B) There is no computation of Life Expectancy nor Life Table.
1041:
1042: Revision 1.97 2004/02/20 13:25:42 lievre
1043: Version 0.96d. Population forecasting command line is (temporarily)
1044: suppressed.
1045:
1046: Revision 1.96 2003/07/15 15:38:55 brouard
1047: * imach.c (Repository): Errors in subdirf, 2, 3 while printing tmpout is
1048: rewritten within the same printf. Workaround: many printfs.
1049:
1050: Revision 1.95 2003/07/08 07:54:34 brouard
1051: * imach.c (Repository):
1052: (Repository): Using imachwizard code to output a more meaningful covariance
1053: matrix (cov(a12,c31) instead of numbers.
1054:
1055: Revision 1.94 2003/06/27 13:00:02 brouard
1056: Just cleaning
1057:
1058: Revision 1.93 2003/06/25 16:33:55 brouard
1059: (Module): On windows (cygwin) function asctime_r doesn't
1060: exist so I changed back to asctime which exists.
1061: (Module): Version 0.96b
1062:
1063: Revision 1.92 2003/06/25 16:30:45 brouard
1064: (Module): On windows (cygwin) function asctime_r doesn't
1065: exist so I changed back to asctime which exists.
1066:
1067: Revision 1.91 2003/06/25 15:30:29 brouard
1068: * imach.c (Repository): Duplicated warning errors corrected.
1069: (Repository): Elapsed time after each iteration is now output. It
1070: helps to forecast when convergence will be reached. Elapsed time
1071: is stamped in powell. We created a new html file for the graphs
1072: concerning matrix of covariance. It has extension -cov.htm.
1073:
1074: Revision 1.90 2003/06/24 12:34:15 brouard
1075: (Module): Some bugs corrected for windows. Also, when
1076: mle=-1 a template is output in file "or"mypar.txt with the design
1077: of the covariance matrix to be input.
1078:
1079: Revision 1.89 2003/06/24 12:30:52 brouard
1080: (Module): Some bugs corrected for windows. Also, when
1081: mle=-1 a template is output in file "or"mypar.txt with the design
1082: of the covariance matrix to be input.
1083:
1084: Revision 1.88 2003/06/23 17:54:56 brouard
1085: * imach.c (Repository): Create a sub-directory where all the secondary files are. Only imach, htm, gp and r(imach) are on the main directory. Correct time and other things.
1086:
1087: Revision 1.87 2003/06/18 12:26:01 brouard
1088: Version 0.96
1089:
1090: Revision 1.86 2003/06/17 20:04:08 brouard
1091: (Module): Change position of html and gnuplot routines and added
1092: routine fileappend.
1093:
1094: Revision 1.85 2003/06/17 13:12:43 brouard
1095: * imach.c (Repository): Check when date of death was earlier that
1096: current date of interview. It may happen when the death was just
1097: prior to the death. In this case, dh was negative and likelihood
1098: was wrong (infinity). We still send an "Error" but patch by
1099: assuming that the date of death was just one stepm after the
1100: interview.
1101: (Repository): Because some people have very long ID (first column)
1102: we changed int to long in num[] and we added a new lvector for
1103: memory allocation. But we also truncated to 8 characters (left
1104: truncation)
1105: (Repository): No more line truncation errors.
1106:
1107: Revision 1.84 2003/06/13 21:44:43 brouard
1108: * imach.c (Repository): Replace "freqsummary" at a correct
1109: place. It differs from routine "prevalence" which may be called
1110: many times. Probs is memory consuming and must be used with
1111: parcimony.
1112: Version 0.95a3 (should output exactly the same maximization than 0.8a2)
1113:
1114: Revision 1.83 2003/06/10 13:39:11 lievre
1115: *** empty log message ***
1116:
1117: Revision 1.82 2003/06/05 15:57:20 brouard
1118: Add log in imach.c and fullversion number is now printed.
1119:
1120: */
1121: /*
1122: Interpolated Markov Chain
1123:
1124: Short summary of the programme:
1125:
1.227 brouard 1126: This program computes Healthy Life Expectancies or State-specific
1127: (if states aren't health statuses) Expectancies from
1128: cross-longitudinal data. Cross-longitudinal data consist in:
1129:
1130: -1- a first survey ("cross") where individuals from different ages
1131: are interviewed on their health status or degree of disability (in
1132: the case of a health survey which is our main interest)
1133:
1134: -2- at least a second wave of interviews ("longitudinal") which
1135: measure each change (if any) in individual health status. Health
1136: expectancies are computed from the time spent in each health state
1137: according to a model. More health states you consider, more time is
1138: necessary to reach the Maximum Likelihood of the parameters involved
1139: in the model. The simplest model is the multinomial logistic model
1140: where pij is the probability to be observed in state j at the second
1141: wave conditional to be observed in state i at the first
1142: wave. Therefore the model is: log(pij/pii)= aij + bij*age+ cij*sex +
1143: etc , where 'age' is age and 'sex' is a covariate. If you want to
1144: have a more complex model than "constant and age", you should modify
1145: the program where the markup *Covariates have to be included here
1146: again* invites you to do it. More covariates you add, slower the
1.126 brouard 1147: convergence.
1148:
1149: The advantage of this computer programme, compared to a simple
1150: multinomial logistic model, is clear when the delay between waves is not
1151: identical for each individual. Also, if a individual missed an
1152: intermediate interview, the information is lost, but taken into
1153: account using an interpolation or extrapolation.
1154:
1155: hPijx is the probability to be observed in state i at age x+h
1156: conditional to the observed state i at age x. The delay 'h' can be
1157: split into an exact number (nh*stepm) of unobserved intermediate
1158: states. This elementary transition (by month, quarter,
1159: semester or year) is modelled as a multinomial logistic. The hPx
1160: matrix is simply the matrix product of nh*stepm elementary matrices
1161: and the contribution of each individual to the likelihood is simply
1162: hPijx.
1163:
1164: Also this programme outputs the covariance matrix of the parameters but also
1.218 brouard 1165: of the life expectancies. It also computes the period (stable) prevalence.
1166:
1167: Back prevalence and projections:
1.227 brouard 1168:
1169: - back_prevalence_limit(double *p, double **bprlim, double ageminpar,
1170: double agemaxpar, double ftolpl, int *ncvyearp, double
1171: dateprev1,double dateprev2, int firstpass, int lastpass, int
1172: mobilavproj)
1173:
1174: Computes the back prevalence limit for any combination of
1175: covariate values k at any age between ageminpar and agemaxpar and
1176: returns it in **bprlim. In the loops,
1177:
1178: - **bprevalim(**bprlim, ***mobaverage, nlstate, *p, age, **oldm,
1179: **savm, **dnewm, **doldm, **dsavm, ftolpl, ncvyearp, k);
1180:
1181: - hBijx Back Probability to be in state i at age x-h being in j at x
1.218 brouard 1182: Computes for any combination of covariates k and any age between bage and fage
1183: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
1184: oldm=oldms;savm=savms;
1.227 brouard 1185:
1.267 brouard 1186: - hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
1.218 brouard 1187: Computes the transition matrix starting at age 'age' over
1188: 'nhstepm*hstepm*stepm' months (i.e. until
1189: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
1.227 brouard 1190: nhstepm*hstepm matrices.
1191:
1192: Returns p3mat[i][j][h] after calling
1193: p3mat[i][j][h]=matprod2(newm,
1194: bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm,
1195: dsavm,ij),\ 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
1196: oldm);
1.226 brouard 1197:
1198: Important routines
1199:
1200: - func (or funcone), computes logit (pij) distinguishing
1201: o fixed variables (single or product dummies or quantitative);
1202: o varying variables by:
1203: (1) wave (single, product dummies, quantitative),
1204: (2) by age (can be month) age (done), age*age (done), age*Vn where Vn can be:
1205: % fixed dummy (treated) or quantitative (not done because time-consuming);
1206: % varying dummy (not done) or quantitative (not done);
1207: - Tricode which tests the modality of dummy variables (in order to warn with wrong or empty modalities)
1208: and returns the number of efficient covariates cptcoveff and modalities nbcode[Tvar[k]][1]= 0 and nbcode[Tvar[k]][2]= 1 usually.
1209: - printinghtml which outputs results like life expectancy in and from a state for a combination of modalities of dummy variables
1.325 brouard 1210: o There are 2**cptcoveff combinations of (0,1) for cptcoveff variables. Outputting only combinations with people, éliminating 1 1 if
1.226 brouard 1211: race White (0 0), Black vs White (1 0), Hispanic (0 1) and 1 1 being meaningless.
1.218 brouard 1212:
1.226 brouard 1213:
1214:
1.324 brouard 1215: Authors: Nicolas Brouard (brouard@ined.fr) and Agnès Lièvre (lievre@ined.fr).
1216: Institut national d'études démographiques, Paris.
1.126 brouard 1217: This software have been partly granted by Euro-REVES, a concerted action
1218: from the European Union.
1219: It is copyrighted identically to a GNU software product, ie programme and
1220: software can be distributed freely for non commercial use. Latest version
1221: can be accessed at http://euroreves.ined.fr/imach .
1222:
1223: Help to debug: LD_PRELOAD=/usr/local/lib/libnjamd.so ./imach foo.imach
1224: or better on gdb : set env LD_PRELOAD=/usr/local/lib/libnjamd.so
1225:
1226: **********************************************************************/
1227: /*
1228: main
1229: read parameterfile
1230: read datafile
1231: concatwav
1232: freqsummary
1233: if (mle >= 1)
1234: mlikeli
1235: print results files
1236: if mle==1
1237: computes hessian
1238: read end of parameter file: agemin, agemax, bage, fage, estepm
1239: begin-prev-date,...
1240: open gnuplot file
1241: open html file
1.145 brouard 1242: period (stable) prevalence | pl_nom 1-1 2-2 etc by covariate
1243: for age prevalim() | #****** V1=0 V2=1 V3=1 V4=0 ******
1244: | 65 1 0 2 1 3 1 4 0 0.96326 0.03674
1245: freexexit2 possible for memory heap.
1246:
1247: h Pij x | pij_nom ficrestpij
1248: # Cov Agex agex+h hpijx with i,j= 1-1 1-2 1-3 2-1 2-2 2-3
1249: 1 85 85 1.00000 0.00000 0.00000 0.00000 1.00000 0.00000
1250: 1 85 86 0.68299 0.22291 0.09410 0.71093 0.00000 0.28907
1251:
1252: 1 65 99 0.00364 0.00322 0.99314 0.00350 0.00310 0.99340
1253: 1 65 100 0.00214 0.00204 0.99581 0.00206 0.00196 0.99597
1254: variance of p one-step probabilities varprob | prob_nom ficresprob #One-step probabilities and stand. devi in ()
1255: Standard deviation of one-step probabilities | probcor_nom ficresprobcor #One-step probabilities and correlation matrix
1256: Matrix of variance covariance of one-step probabilities | probcov_nom ficresprobcov #One-step probabilities and covariance matrix
1257:
1.126 brouard 1258: forecasting if prevfcast==1 prevforecast call prevalence()
1259: health expectancies
1260: Variance-covariance of DFLE
1261: prevalence()
1262: movingaverage()
1263: varevsij()
1264: if popbased==1 varevsij(,popbased)
1265: total life expectancies
1266: Variance of period (stable) prevalence
1267: end
1268: */
1269:
1.187 brouard 1270: /* #define DEBUG */
1271: /* #define DEBUGBRENT */
1.203 brouard 1272: /* #define DEBUGLINMIN */
1273: /* #define DEBUGHESS */
1274: #define DEBUGHESSIJ
1.224 brouard 1275: /* #define LINMINORIGINAL /\* Don't use loop on scale in linmin (accepting nan) *\/ */
1.165 brouard 1276: #define POWELL /* Instead of NLOPT */
1.224 brouard 1277: #define POWELLNOF3INFF1TEST /* Skip test */
1.186 brouard 1278: /* #define POWELLORIGINAL /\* Don't use Directest to decide new direction but original Powell test *\/ */
1279: /* #define MNBRAKORIGINAL /\* Don't use mnbrak fix *\/ */
1.319 brouard 1280: /* #define FLATSUP *//* Suppresses directions where likelihood is flat */
1.126 brouard 1281:
1282: #include <math.h>
1283: #include <stdio.h>
1284: #include <stdlib.h>
1285: #include <string.h>
1.226 brouard 1286: #include <ctype.h>
1.159 brouard 1287:
1288: #ifdef _WIN32
1289: #include <io.h>
1.172 brouard 1290: #include <windows.h>
1291: #include <tchar.h>
1.159 brouard 1292: #else
1.126 brouard 1293: #include <unistd.h>
1.159 brouard 1294: #endif
1.126 brouard 1295:
1296: #include <limits.h>
1297: #include <sys/types.h>
1.171 brouard 1298:
1299: #if defined(__GNUC__)
1300: #include <sys/utsname.h> /* Doesn't work on Windows */
1301: #endif
1302:
1.126 brouard 1303: #include <sys/stat.h>
1304: #include <errno.h>
1.159 brouard 1305: /* extern int errno; */
1.126 brouard 1306:
1.157 brouard 1307: /* #ifdef LINUX */
1308: /* #include <time.h> */
1309: /* #include "timeval.h" */
1310: /* #else */
1311: /* #include <sys/time.h> */
1312: /* #endif */
1313:
1.126 brouard 1314: #include <time.h>
1315:
1.136 brouard 1316: #ifdef GSL
1317: #include <gsl/gsl_errno.h>
1318: #include <gsl/gsl_multimin.h>
1319: #endif
1320:
1.167 brouard 1321:
1.162 brouard 1322: #ifdef NLOPT
1323: #include <nlopt.h>
1324: typedef struct {
1325: double (* function)(double [] );
1326: } myfunc_data ;
1327: #endif
1328:
1.126 brouard 1329: /* #include <libintl.h> */
1330: /* #define _(String) gettext (String) */
1331:
1.349 brouard 1332: #define MAXLINE 16384 /* Was 256 and 1024 and 2048. Overflow with 312 with 2 states and 4 covariates. Should be ok */
1.126 brouard 1333:
1334: #define GNUPLOTPROGRAM "gnuplot"
1.343 brouard 1335: #define GNUPLOTVERSION 5.1
1336: double gnuplotversion=GNUPLOTVERSION;
1.126 brouard 1337: /*#define GNUPLOTPROGRAM "..\\gp37mgw\\wgnuplot"*/
1.329 brouard 1338: #define FILENAMELENGTH 256
1.126 brouard 1339:
1340: #define GLOCK_ERROR_NOPATH -1 /* empty path */
1341: #define GLOCK_ERROR_GETCWD -2 /* cannot get cwd */
1342:
1.349 brouard 1343: #define MAXPARM 216 /**< Maximum number of parameters for the optimization was 128 */
1.144 brouard 1344: #define NPARMAX 64 /**< (nlstate+ndeath-1)*nlstate*ncovmodel */
1.126 brouard 1345:
1346: #define NINTERVMAX 8
1.144 brouard 1347: #define NLSTATEMAX 8 /**< Maximum number of live states (for func) */
1348: #define NDEATHMAX 8 /**< Maximum number of dead states (for func) */
1.325 brouard 1349: #define NCOVMAX 30 /**< Maximum number of covariates used in the model, including generated covariates V1*V2 or V1*age */
1.197 brouard 1350: #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.211 brouard 1351: /*#define decodtabm(h,k,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (k-1)) & 1) +1 : -1)*/
1352: #define decodtabm(h,k,cptcoveff) (((h-1) >> (k-1)) & 1) +1
1.290 brouard 1353: /*#define MAXN 20000 */ /* Should by replaced by nobs, real number of observations and unlimited */
1.144 brouard 1354: #define YEARM 12. /**< Number of months per year */
1.218 brouard 1355: /* #define AGESUP 130 */
1.288 brouard 1356: /* #define AGESUP 150 */
1357: #define AGESUP 200
1.268 brouard 1358: #define AGEINF 0
1.218 brouard 1359: #define AGEMARGE 25 /* Marge for agemin and agemax for(iage=agemin-AGEMARGE; iage <= agemax+3+AGEMARGE; iage++) */
1.126 brouard 1360: #define AGEBASE 40
1.194 brouard 1361: #define AGEOVERFLOW 1.e20
1.164 brouard 1362: #define AGEGOMP 10 /**< Minimal age for Gompertz adjustment */
1.157 brouard 1363: #ifdef _WIN32
1364: #define DIRSEPARATOR '\\'
1365: #define CHARSEPARATOR "\\"
1366: #define ODIRSEPARATOR '/'
1367: #else
1.126 brouard 1368: #define DIRSEPARATOR '/'
1369: #define CHARSEPARATOR "/"
1370: #define ODIRSEPARATOR '\\'
1371: #endif
1372:
1.354 ! brouard 1373: /* $Id: imach.c,v 1.353 2023/05/08 18:48:22 brouard Exp $ */
1.126 brouard 1374: /* $State: Exp $ */
1.196 brouard 1375: #include "version.h"
1376: char version[]=__IMACH_VERSION__;
1.352 brouard 1377: char copyright[]="April 2023,INED-EUROREVES-Institut de longevite-Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research 25293121), Intel Software 2015-2020, Nihon University 2021-202, INED 2000-2022";
1.354 ! brouard 1378: char fullversion[]="$Revision: 1.353 $ $Date: 2023/05/08 18:48:22 $";
1.126 brouard 1379: char strstart[80];
1380: char optionfilext[10], optionfilefiname[FILENAMELENGTH];
1.130 brouard 1381: int erreur=0, nberr=0, nbwarn=0; /* Error number, number of errors number of warnings */
1.342 brouard 1382: int debugILK=0; /* debugILK is set by a #d in a comment line */
1.187 brouard 1383: int nagesqr=0, nforce=0; /* nagesqr=1 if model is including age*age, number of forces */
1.330 brouard 1384: /* Number of covariates model (1)=V2+V1+ V3*age+V2*V4 */
1385: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
1.335 brouard 1386: int cptcovn=0; /**< cptcovn decodemodel: number of covariates k of the models excluding age*products =6 and age*age but including products */
1.330 brouard 1387: int cptcovt=0; /**< cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
1.335 brouard 1388: int cptcovs=0; /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
1389: int cptcovsnq=0; /**< cptcovsnq number of SIMPLE covariates in the model but non quantitative V2+V1 =2 */
1.145 brouard 1390: int cptcovage=0; /**< Number of covariates with age: V3*age only =1 */
1.349 brouard 1391: int cptcovprodage=0; /**< Number of fixed covariates with age: V3*age or V2*V3*age 1 */
1392: int cptcovprodvage=0; /**< Number of varying covariates with age: V7*age or V7*V6*age */
1393: int cptcovdageprod=0; /**< Number of doubleproducts with age, since 0.99r44 only: age*Vn*Vm for gnuplot printing*/
1.145 brouard 1394: int cptcovprodnoage=0; /**< Number of covariate products without age */
1.335 brouard 1395: int cptcoveff=0; /* Total number of single dummy covariates (fixed or time varying) to vary for printing results (2**cptcoveff combinations of dummies)(computed in tricode as cptcov) */
1.233 brouard 1396: int ncovf=0; /* Total number of effective fixed covariates (dummy or quantitative) in the model */
1397: int ncovv=0; /* Total number of effective (wave) varying covariates (dummy or quantitative) in the model */
1.339 brouard 1398: int ncovvt=0; /* Total number of effective (wave) varying covariates (dummy or quantitative or products [without age]) in the model */
1.349 brouard 1399: int ncovvta=0; /* +age*V6 + age*V7+ age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of expandend products [with age]) in the model */
1400: int ncovta=0; /*age*V3*V2 +age*V2+agev3+ageV4 +age*V6 + age*V7+ age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of expandend products [with age]) in the model */
1401: int ncova=0; /* Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1402: int ncovva=0; /* +age*V6 + age*V7+ge*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 Total number of effective (wave and stepm) varying with age covariates (single or product, dummy or quantitative) in the model */
1.234 brouard 1403: int nsd=0; /**< Total number of single dummy variables (output) */
1404: int nsq=0; /**< Total number of single quantitative variables (output) */
1.232 brouard 1405: int ncoveff=0; /* Total number of effective fixed dummy covariates in the model */
1.225 brouard 1406: int nqfveff=0; /**< nqfveff Number of Quantitative Fixed Variables Effective */
1.224 brouard 1407: int ntveff=0; /**< ntveff number of effective time varying variables */
1408: int nqtveff=0; /**< ntqveff number of effective time varying quantitative variables */
1.145 brouard 1409: int cptcov=0; /* Working variable */
1.334 brouard 1410: int firstobs=1, lastobs=10; /* nobs = lastobs-firstobs+1 declared globally ;*/
1.290 brouard 1411: int nobs=10; /* Number of observations in the data lastobs-firstobs */
1.218 brouard 1412: int ncovcombmax=NCOVMAX; /* Maximum calculated number of covariate combination = pow(2, cptcoveff) */
1.302 brouard 1413: int npar=NPARMAX; /* Number of parameters (nlstate+ndeath-1)*nlstate*ncovmodel; */
1.126 brouard 1414: int nlstate=2; /* Number of live states */
1415: int ndeath=1; /* Number of dead states */
1.130 brouard 1416: int ncovmodel=0, ncovcol=0; /* Total number of covariables including constant a12*1 +b12*x ncovmodel=2 */
1.339 brouard 1417: int nqv=0, ntv=0, nqtv=0; /* Total number of quantitative variables, time variable (dummy), quantitative and time variable*/
1418: int ncovcolt=0; /* ncovcolt=ncovcol+nqv+ntv+nqtv; total of covariates in the data, not in the model equation*/
1.126 brouard 1419: int popbased=0;
1420:
1421: int *wav; /* Number of waves for this individuual 0 is possible */
1.130 brouard 1422: int maxwav=0; /* Maxim number of waves */
1423: int jmin=0, jmax=0; /* min, max spacing between 2 waves */
1424: int ijmin=0, ijmax=0; /* Individuals having jmin and jmax */
1425: int gipmx=0, gsw=0; /* Global variables on the number of contributions
1.126 brouard 1426: to the likelihood and the sum of weights (done by funcone)*/
1.130 brouard 1427: int mle=1, weightopt=0;
1.126 brouard 1428: int **mw; /* mw[mi][i] is number of the mi wave for this individual */
1429: int **dh; /* dh[mi][i] is number of steps between mi,mi+1 for this individual */
1430: int **bh; /* bh[mi][i] is the bias (+ or -) for this individual if the delay between
1431: * wave mi and wave mi+1 is not an exact multiple of stepm. */
1.162 brouard 1432: int countcallfunc=0; /* Count the number of calls to func */
1.230 brouard 1433: int selected(int kvar); /* Is covariate kvar selected for printing results */
1434:
1.130 brouard 1435: double jmean=1; /* Mean space between 2 waves */
1.145 brouard 1436: double **matprod2(); /* test */
1.126 brouard 1437: double **oldm, **newm, **savm; /* Working pointers to matrices */
1438: double **oldms, **newms, **savms; /* Fixed working pointers to matrices */
1.218 brouard 1439: double **ddnewms, **ddoldms, **ddsavms; /* for freeing later */
1440:
1.136 brouard 1441: /*FILE *fic ; */ /* Used in readdata only */
1.217 brouard 1442: FILE *ficpar, *ficparo,*ficres, *ficresp, *ficresphtm, *ficresphtmfr, *ficrespl, *ficresplb,*ficrespij, *ficrespijb, *ficrest,*ficresf, *ficresfb,*ficrespop;
1.126 brouard 1443: FILE *ficlog, *ficrespow;
1.130 brouard 1444: int globpr=0; /* Global variable for printing or not */
1.126 brouard 1445: double fretone; /* Only one call to likelihood */
1.130 brouard 1446: long ipmx=0; /* Number of contributions */
1.126 brouard 1447: double sw; /* Sum of weights */
1448: char filerespow[FILENAMELENGTH];
1449: char fileresilk[FILENAMELENGTH]; /* File of individual contributions to the likelihood */
1450: FILE *ficresilk;
1451: FILE *ficgp,*ficresprob,*ficpop, *ficresprobcov, *ficresprobcor;
1452: FILE *ficresprobmorprev;
1453: FILE *fichtm, *fichtmcov; /* Html File */
1454: FILE *ficreseij;
1455: char filerese[FILENAMELENGTH];
1456: FILE *ficresstdeij;
1457: char fileresstde[FILENAMELENGTH];
1458: FILE *ficrescveij;
1459: char filerescve[FILENAMELENGTH];
1460: FILE *ficresvij;
1461: char fileresv[FILENAMELENGTH];
1.269 brouard 1462:
1.126 brouard 1463: char title[MAXLINE];
1.234 brouard 1464: char model[MAXLINE]; /**< The model line */
1.217 brouard 1465: char optionfile[FILENAMELENGTH], datafile[FILENAMELENGTH], filerespl[FILENAMELENGTH], fileresplb[FILENAMELENGTH];
1.126 brouard 1466: char plotcmd[FILENAMELENGTH], pplotcmd[FILENAMELENGTH];
1467: char tmpout[FILENAMELENGTH], tmpout2[FILENAMELENGTH];
1468: char command[FILENAMELENGTH];
1469: int outcmd=0;
1470:
1.217 brouard 1471: char fileres[FILENAMELENGTH], filerespij[FILENAMELENGTH], filerespijb[FILENAMELENGTH], filereso[FILENAMELENGTH], rfileres[FILENAMELENGTH];
1.202 brouard 1472: char fileresu[FILENAMELENGTH]; /* fileres without r in front */
1.126 brouard 1473: char filelog[FILENAMELENGTH]; /* Log file */
1474: char filerest[FILENAMELENGTH];
1475: char fileregp[FILENAMELENGTH];
1476: char popfile[FILENAMELENGTH];
1477:
1478: char optionfilegnuplot[FILENAMELENGTH], optionfilehtm[FILENAMELENGTH], optionfilehtmcov[FILENAMELENGTH] ;
1479:
1.157 brouard 1480: /* struct timeval start_time, end_time, curr_time, last_time, forecast_time; */
1481: /* struct timezone tzp; */
1482: /* extern int gettimeofday(); */
1483: struct tm tml, *gmtime(), *localtime();
1484:
1485: extern time_t time();
1486:
1487: struct tm start_time, end_time, curr_time, last_time, forecast_time;
1488: time_t rstart_time, rend_time, rcurr_time, rlast_time, rforecast_time; /* raw time */
1.349 brouard 1489: time_t rlast_btime; /* raw time */
1.157 brouard 1490: struct tm tm;
1491:
1.126 brouard 1492: char strcurr[80], strfor[80];
1493:
1494: char *endptr;
1495: long lval;
1496: double dval;
1497:
1498: #define NR_END 1
1499: #define FREE_ARG char*
1500: #define FTOL 1.0e-10
1501:
1502: #define NRANSI
1.240 brouard 1503: #define ITMAX 200
1504: #define ITPOWMAX 20 /* This is now multiplied by the number of parameters */
1.126 brouard 1505:
1506: #define TOL 2.0e-4
1507:
1508: #define CGOLD 0.3819660
1509: #define ZEPS 1.0e-10
1510: #define SHFT(a,b,c,d) (a)=(b);(b)=(c);(c)=(d);
1511:
1512: #define GOLD 1.618034
1513: #define GLIMIT 100.0
1514: #define TINY 1.0e-20
1515:
1516: static double maxarg1,maxarg2;
1517: #define FMAX(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)>(maxarg2)? (maxarg1):(maxarg2))
1518: #define FMIN(a,b) (maxarg1=(a),maxarg2=(b),(maxarg1)<(maxarg2)? (maxarg1):(maxarg2))
1519:
1520: #define SIGN(a,b) ((b)>0.0 ? fabs(a) : -fabs(a))
1521: #define rint(a) floor(a+0.5)
1.166 brouard 1522: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/myutils_8h-source.html */
1.183 brouard 1523: #define mytinydouble 1.0e-16
1.166 brouard 1524: /* #define DEQUAL(a,b) (fabs((a)-(b))<mytinydouble) */
1525: /* http://www.thphys.uni-heidelberg.de/~robbers/cmbeasy/doc/html/mynrutils_8h-source.html */
1526: /* static double dsqrarg; */
1527: /* #define DSQR(a) (DEQUAL((dsqrarg=(a)),0.0) ? 0.0 : dsqrarg*dsqrarg) */
1.126 brouard 1528: static double sqrarg;
1529: #define SQR(a) ((sqrarg=(a)) == 0.0 ? 0.0 :sqrarg*sqrarg)
1530: #define SWAP(a,b) {temp=(a);(a)=(b);(b)=temp;}
1531: int agegomp= AGEGOMP;
1532:
1533: int imx;
1534: int stepm=1;
1535: /* Stepm, step in month: minimum step interpolation*/
1536:
1537: int estepm;
1538: /* Estepm, step in month to interpolate survival function in order to approximate Life Expectancy*/
1539:
1540: int m,nb;
1541: long *num;
1.197 brouard 1542: int firstpass=0, lastpass=4,*cod, *cens;
1.192 brouard 1543: int *ncodemax; /* ncodemax[j]= Number of modalities of the j th
1544: covariate for which somebody answered excluding
1545: undefined. Usually 2: 0 and 1. */
1546: int *ncodemaxwundef; /* ncodemax[j]= Number of modalities of the j th
1547: covariate for which somebody answered including
1548: undefined. Usually 3: -1, 0 and 1. */
1.126 brouard 1549: double **agev,*moisnais, *annais, *moisdc, *andc,**mint, **anint;
1.218 brouard 1550: double **pmmij, ***probs; /* Global pointer */
1.219 brouard 1551: double ***mobaverage, ***mobaverages; /* New global variable */
1.332 brouard 1552: double **precov; /* New global variable to store for each resultline, values of model covariates given by the resultlines (in order to speed up) */
1.126 brouard 1553: double *ageexmed,*agecens;
1554: double dateintmean=0;
1.296 brouard 1555: double anprojd, mprojd, jprojd; /* For eventual projections */
1556: double anprojf, mprojf, jprojf;
1.126 brouard 1557:
1.296 brouard 1558: double anbackd, mbackd, jbackd; /* For eventual backprojections */
1559: double anbackf, mbackf, jbackf;
1560: double jintmean,mintmean,aintmean;
1.126 brouard 1561: double *weight;
1562: int **s; /* Status */
1.141 brouard 1563: double *agedc;
1.145 brouard 1564: double **covar; /**< covar[j,i], value of jth covariate for individual i,
1.141 brouard 1565: * covar=matrix(0,NCOVMAX,1,n);
1.187 brouard 1566: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*age; */
1.268 brouard 1567: double **coqvar; /* Fixed quantitative covariate nqv */
1.341 brouard 1568: double ***cotvar; /* Time varying covariate start at ncovcol + nqv + (1 to ntv) */
1.225 brouard 1569: double ***cotqvar; /* Time varying quantitative covariate itqv */
1.141 brouard 1570: double idx;
1571: int **nbcode, *Tvar; /**< model=V2 => Tvar[1]= 2 */
1.319 brouard 1572: /* Some documentation */
1573: /* Design original data
1574: * V1 V2 V3 V4 V5 V6 V7 V8 Weight ddb ddth d1st s1 V9 V10 V11 V12 s2 V9 V10 V11 V12
1575: * < ncovcol=6 > nqv=2 (V7 V8) dv dv dv qtv dv dv dvv qtv
1576: * ntv=3 nqtv=1
1.330 brouard 1577: * cptcovn number of covariates (not including constant and age or age*age) = number of plus sign + 1 = 10+1=11
1.319 brouard 1578: * For time varying covariate, quanti or dummies
1579: * cotqvar[wav][iv(1 to nqtv)][i]= [1][12][i]=(V12) quanti
1.341 brouard 1580: * cotvar[wav][ncovcol+nqv+ iv(1 to nqtv)][i]= [(1 to nqtv)][i]=(V12) quanti
1.319 brouard 1581: * cotvar[wav][iv(1 to ntv)][i]= [1][1][i]=(V9) dummies at wav 1
1582: * cotvar[wav][iv(1 to ntv)][i]= [1][2][i]=(V10) dummies at wav 1
1.332 brouard 1583: * covar[Vk,i], value of the Vkth fixed covariate dummy or quanti for individual i:
1.319 brouard 1584: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
1585: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 + V9 + V9*age + V10
1586: * k= 1 2 3 4 5 6 7 8 9 10 11
1587: */
1588: /* According to the model, more columns can be added to covar by the product of covariates */
1.318 brouard 1589: /* ncovcol=1(Males=0 Females=1) nqv=1(raedyrs) ntv=2(withoutiadl=0 withiadl=1, witoutadl=0 withoutadl=1) nqtv=1(bmi) nlstate=3 ndeath=1
1590: # States 1=Coresidence, 2 Living alone, 3 Institution
1591: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1592: */
1.349 brouard 1593: /* V5+V4+ V3+V4*V3 +V5*age+V2 +V1*V2+V1*age+V1+V4*V3*age */
1594: /* kmodel 1 2 3 4 5 6 7 8 9 10 */
1595: /*Typevar[k]= 0 0 0 2 1 0 2 1 0 3 *//*0 for simple covariate (dummy, quantitative,*/
1596: /* fixed or varying), 1 for age product, 2 for*/
1597: /* product without age, 3 for age and double product */
1598: /*Dummy[k]= 1 0 0 1 3 1 1 2 0 3 *//*Dummy[k] 0=dummy (0 1), 1 quantitative */
1599: /*(single or product without age), 2 dummy*/
1600: /* with age product, 3 quant with age product*/
1601: /*Tvar[k]= 5 4 3 6 5 2 7 1 1 6 */
1602: /* nsd 1 2 3 */ /* Counting single dummies covar fixed or tv */
1603: /*TnsdVar[Tvar] 1 2 3 */
1604: /*Tvaraff[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1605: /*TvarsD[nsd] 4 3 1 */ /* ID of single dummy cova fixed or timevary*/
1606: /*TvarsDind[nsd] 2 3 9 */ /* position K of single dummy cova */
1607: /* nsq 1 2 */ /* Counting single quantit tv */
1608: /* TvarsQ[k] 5 2 */ /* Number of single quantitative cova */
1609: /* TvarsQind 1 6 */ /* position K of single quantitative cova */
1610: /* Tprod[i]=k 1 2 */ /* Position in model of the ith prod without age */
1611: /* cptcovage 1 2 3 */ /* Counting cov*age in the model equation */
1612: /* Tage[cptcovage]=k 5 8 10 */ /* Position in the model of ith cov*age */
1.350 brouard 1613: /* model="V2+V3+V4+V6+V7+V6*V2+V7*V2+V6*V3+V7*V3+V6*V4+V7*V4+age*V2+age*V3+age*V4+age*V6+age*V7+age*V6*V2+age*V6*V3+age*V7*V3+age*V6*V4+age*V7*V4\r"*/
1614: /* p Tvard[1][1]@21 = {6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0}*/
1.354 ! brouard 1615: /* p Tvard[2][1]@21 = {7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0 <repeats 11 times>} */
1.350 brouard 1616: /* p Tvardk[1][1]@24 = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0}*/
1617: /* p Tvardk[1][1]@22 = {0, 0, 0, 0, 0, 0, 0, 0, 6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4, 0, 0} */
1.349 brouard 1618: /* Tvard[1][1]@4={4,3,1,2} V4*V3 V1*V2 */ /* Position in model of the ith prod without age */
1.330 brouard 1619: /* Tvardk[4][1]=4;Tvardk[4][2]=3;Tvardk[7][1]=1;Tvardk[7][2]=2 */ /* Variables of a prod at position in the model equation*/
1.319 brouard 1620: /* TvarF TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 ID of fixed covariates or product V2, V1*V2, V1 */
1.320 brouard 1621: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.234 brouard 1622: /* Type */
1623: /* V 1 2 3 4 5 */
1624: /* F F V V V */
1625: /* D Q D D Q */
1626: /* */
1627: int *TvarsD;
1.330 brouard 1628: int *TnsdVar;
1.234 brouard 1629: int *TvarsDind;
1630: int *TvarsQ;
1631: int *TvarsQind;
1632:
1.318 brouard 1633: #define MAXRESULTLINESPONE 10+1
1.235 brouard 1634: int nresult=0;
1.258 brouard 1635: int parameterline=0; /* # of the parameter (type) line */
1.334 brouard 1636: int TKresult[MAXRESULTLINESPONE]; /* TKresult[nres]=k for each resultline nres give the corresponding combination of dummies */
1637: int resultmodel[MAXRESULTLINESPONE][NCOVMAX];/* resultmodel[k1]=k3: k1th position in the model corresponds to the k3 position in the resultline */
1638: int modelresult[MAXRESULTLINESPONE][NCOVMAX];/* modelresult[k3]=k1: k1th position in the model corresponds to the k3 position in the resultline */
1639: int Tresult[MAXRESULTLINESPONE][NCOVMAX];/* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1640: int Tinvresult[MAXRESULTLINESPONE][NCOVMAX];/* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1641: double TinvDoQresult[MAXRESULTLINESPONE][NCOVMAX];/* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.334 brouard 1642: int Tvresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 1643: double Tqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.318 brouard 1644: double Tqinvresult[MAXRESULTLINESPONE][NCOVMAX]; /* For quantitative variable , value (output) */
1.332 brouard 1645: int Tvqresult[MAXRESULTLINESPONE][NCOVMAX]; /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.318 brouard 1646:
1647: /* ncovcol=1(Males=0 Females=1) nqv=1(raedyrs) ntv=2(withoutiadl=0 withiadl=1, witoutadl=0 withoutadl=1) nqtv=1(bmi) nlstate=3 ndeath=1
1648: # States 1=Coresidence, 2 Living alone, 3 Institution
1649: # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi
1650: */
1.234 brouard 1651: /* int *TDvar; /\**< TDvar[1]=4, TDvarF[2]=3, TDvar[3]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
1.232 brouard 1652: int *TvarF; /**< TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1653: int *TvarFind; /**< TvarFind[1]=6, TvarFind[2]=7, Tvarind[3]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1654: int *TvarV; /**< TvarV[1]=Tvar[1]=5, TvarV[2]=Tvar[2]=4 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1655: int *TvarVind; /**< TvarVind[1]=1, TvarVind[2]=2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1656: int *TvarA; /**< TvarA[1]=Tvar[5]=5, TvarA[2]=Tvar[8]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1657: int *TvarAind; /**< TvarindA[1]=5, TvarAind[2]=8 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.231 brouard 1658: int *TvarFD; /**< TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1659: int *TvarFDind; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1660: int *TvarFQ; /* TvarFQ[1]=V2 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1661: int *TvarFQind; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1662: int *TvarVD; /* TvarVD[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1663: int *TvarVDind; /* TvarVDind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1664: int *TvarVQ; /* TvarVQ[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
1665: int *TvarVQind; /* TvarVQind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
1.339 brouard 1666: int *TvarVV; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1667: int *TvarVVind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1.349 brouard 1668: int *TvarVVA; /* We count ncovvt time varying covariates (single or products with age) and put their name into TvarVVA */
1669: int *TvarVVAind; /* We count ncovvt time varying covariates (single or products without age) and put their name into TvarVV */
1670: int *TvarAVVA; /* We count ALL ncovta time varying covariates (single or products with age) and put their name into TvarVVA */
1671: int *TvarAVVAind; /* We count ALL ncovta time varying covariates (single or products without age) and put their name into TvarVV */
1.339 brouard 1672: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 1673: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age */
1674: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
1675: /* TvarVV={3,1,3,1,3}, for V3 and then the product V1*V3 is decomposed into V1 and V3 */
1676: /* TvarVVind={2,5,5,6,6}, for V3 and then the product V1*V3 is decomposed into V1 and V3 and V1*V3*age into 6,6 */
1.230 brouard 1677: int *Tvarsel; /**< Selected covariates for output */
1678: double *Tvalsel; /**< Selected modality value of covariate for output */
1.349 brouard 1679: int *Typevar; /**< 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 age*Vn*Vm */
1.227 brouard 1680: int *Fixed; /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
1681: int *Dummy; /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
1.238 brouard 1682: int *DummyV; /** Dummy[v] 0=dummy (0 1), 1 quantitative */
1683: int *FixedV; /** FixedV[v] 0 fixed, 1 varying */
1.197 brouard 1684: int *Tage;
1.227 brouard 1685: int anyvaryingduminmodel=0; /**< Any varying dummy in Model=1 yes, 0 no, to avoid a loop on waves in freq */
1.228 brouard 1686: int *Tmodelind; /** Tmodelind[Tvaraff[3]]=9 for V1 position,Tvaraff[1]@9={4, 3, 1, 0, 0, 0, 0, 0, 0}, model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.230 brouard 1687: int *TmodelInvind; /** Tmodelind[Tvaraff[3]]=9 for V1 position,Tvaraff[1]@9={4, 3, 1, 0, 0, 0, 0, 0, 0}, model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1688: int *TmodelInvQind; /** Tmodelqind[1]=1 for V5(quantitative varying) position,Tvaraff[1]@9={4, 3, 1, 0, 0, 0, 0, 0, 0}, model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.145 brouard 1689: int *Ndum; /** Freq of modality (tricode */
1.200 brouard 1690: /* int **codtab;*/ /**< codtab=imatrix(1,100,1,10); */
1.227 brouard 1691: int **Tvard;
1.330 brouard 1692: int **Tvardk;
1.227 brouard 1693: int *Tprod;/**< Gives the k position of the k1 product */
1.238 brouard 1694: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3 */
1.227 brouard 1695: int *Tposprod; /**< Gives the k1 product from the k position */
1.238 brouard 1696: /* if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2) */
1697: /* Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5(V3*V2)]=2 (2nd product without age) */
1.227 brouard 1698: int cptcovprod, *Tvaraff, *invalidvarcomb;
1.126 brouard 1699: double *lsurv, *lpop, *tpop;
1700:
1.231 brouard 1701: #define FD 1; /* Fixed dummy covariate */
1702: #define FQ 2; /* Fixed quantitative covariate */
1703: #define FP 3; /* Fixed product covariate */
1704: #define FPDD 7; /* Fixed product dummy*dummy covariate */
1705: #define FPDQ 8; /* Fixed product dummy*quantitative covariate */
1706: #define FPQQ 9; /* Fixed product quantitative*quantitative covariate */
1707: #define VD 10; /* Varying dummy covariate */
1708: #define VQ 11; /* Varying quantitative covariate */
1709: #define VP 12; /* Varying product covariate */
1710: #define VPDD 13; /* Varying product dummy*dummy covariate */
1711: #define VPDQ 14; /* Varying product dummy*quantitative covariate */
1712: #define VPQQ 15; /* Varying product quantitative*quantitative covariate */
1713: #define APFD 16; /* Age product * fixed dummy covariate */
1714: #define APFQ 17; /* Age product * fixed quantitative covariate */
1715: #define APVD 18; /* Age product * varying dummy covariate */
1716: #define APVQ 19; /* Age product * varying quantitative covariate */
1717:
1718: #define FTYPE 1; /* Fixed covariate */
1719: #define VTYPE 2; /* Varying covariate (loop in wave) */
1720: #define ATYPE 2; /* Age product covariate (loop in dh within wave)*/
1721:
1722: struct kmodel{
1723: int maintype; /* main type */
1724: int subtype; /* subtype */
1725: };
1726: struct kmodel modell[NCOVMAX];
1727:
1.143 brouard 1728: double ftol=FTOL; /**< Tolerance for computing Max Likelihood */
1729: double ftolhess; /**< Tolerance for computing hessian */
1.126 brouard 1730:
1731: /**************** split *************************/
1732: static int split( char *path, char *dirc, char *name, char *ext, char *finame )
1733: {
1734: /* From a file name with (full) path (either Unix or Windows) we extract the directory (dirc)
1735: the name of the file (name), its extension only (ext) and its first part of the name (finame)
1736: */
1737: char *ss; /* pointer */
1.186 brouard 1738: int l1=0, l2=0; /* length counters */
1.126 brouard 1739:
1740: l1 = strlen(path ); /* length of path */
1741: if ( l1 == 0 ) return( GLOCK_ERROR_NOPATH );
1742: ss= strrchr( path, DIRSEPARATOR ); /* find last / */
1743: if ( ss == NULL ) { /* no directory, so determine current directory */
1744: strcpy( name, path ); /* we got the fullname name because no directory */
1745: /*if(strrchr(path, ODIRSEPARATOR )==NULL)
1746: printf("Warning you should use %s as a separator\n",DIRSEPARATOR);*/
1747: /* get current working directory */
1748: /* extern char* getcwd ( char *buf , int len);*/
1.184 brouard 1749: #ifdef WIN32
1750: if (_getcwd( dirc, FILENAME_MAX ) == NULL ) {
1751: #else
1752: if (getcwd(dirc, FILENAME_MAX) == NULL) {
1753: #endif
1.126 brouard 1754: return( GLOCK_ERROR_GETCWD );
1755: }
1756: /* got dirc from getcwd*/
1757: printf(" DIRC = %s \n",dirc);
1.205 brouard 1758: } else { /* strip directory from path */
1.126 brouard 1759: ss++; /* after this, the filename */
1760: l2 = strlen( ss ); /* length of filename */
1761: if ( l2 == 0 ) return( GLOCK_ERROR_NOPATH );
1762: strcpy( name, ss ); /* save file name */
1763: strncpy( dirc, path, l1 - l2 ); /* now the directory */
1.186 brouard 1764: dirc[l1-l2] = '\0'; /* add zero */
1.126 brouard 1765: printf(" DIRC2 = %s \n",dirc);
1766: }
1767: /* We add a separator at the end of dirc if not exists */
1768: l1 = strlen( dirc ); /* length of directory */
1769: if( dirc[l1-1] != DIRSEPARATOR ){
1770: dirc[l1] = DIRSEPARATOR;
1771: dirc[l1+1] = 0;
1772: printf(" DIRC3 = %s \n",dirc);
1773: }
1774: ss = strrchr( name, '.' ); /* find last / */
1775: if (ss >0){
1776: ss++;
1777: strcpy(ext,ss); /* save extension */
1778: l1= strlen( name);
1779: l2= strlen(ss)+1;
1780: strncpy( finame, name, l1-l2);
1781: finame[l1-l2]= 0;
1782: }
1783:
1784: return( 0 ); /* we're done */
1785: }
1786:
1787:
1788: /******************************************/
1789:
1790: void replace_back_to_slash(char *s, char*t)
1791: {
1792: int i;
1793: int lg=0;
1794: i=0;
1795: lg=strlen(t);
1796: for(i=0; i<= lg; i++) {
1797: (s[i] = t[i]);
1798: if (t[i]== '\\') s[i]='/';
1799: }
1800: }
1801:
1.132 brouard 1802: char *trimbb(char *out, char *in)
1.137 brouard 1803: { /* Trim multiple blanks in line but keeps first blanks if line starts with blanks */
1.132 brouard 1804: char *s;
1805: s=out;
1806: while (*in != '\0'){
1.137 brouard 1807: while( *in == ' ' && *(in+1) == ' '){ /* && *(in+1) != '\0'){*/
1.132 brouard 1808: in++;
1809: }
1810: *out++ = *in++;
1811: }
1812: *out='\0';
1813: return s;
1814: }
1815:
1.351 brouard 1816: char *trimbtab(char *out, char *in)
1817: { /* Trim blanks or tabs in line but keeps first blanks if line starts with blanks */
1818: char *s;
1819: s=out;
1820: while (*in != '\0'){
1821: while( (*in == ' ' || *in == '\t')){ /* && *(in+1) != '\0'){*/
1822: in++;
1823: }
1824: *out++ = *in++;
1825: }
1826: *out='\0';
1827: return s;
1828: }
1829:
1.187 brouard 1830: /* char *substrchaine(char *out, char *in, char *chain) */
1831: /* { */
1832: /* /\* Substract chain 'chain' from 'in', return and output 'out' *\/ */
1833: /* char *s, *t; */
1834: /* t=in;s=out; */
1835: /* while ((*in != *chain) && (*in != '\0')){ */
1836: /* *out++ = *in++; */
1837: /* } */
1838:
1839: /* /\* *in matches *chain *\/ */
1840: /* while ((*in++ == *chain++) && (*in != '\0')){ */
1841: /* printf("*in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1842: /* } */
1843: /* in--; chain--; */
1844: /* while ( (*in != '\0')){ */
1845: /* printf("Bef *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1846: /* *out++ = *in++; */
1847: /* printf("Aft *in = %c, *out= %c *chain= %c \n", *in, *out, *chain); */
1848: /* } */
1849: /* *out='\0'; */
1850: /* out=s; */
1851: /* return out; */
1852: /* } */
1853: char *substrchaine(char *out, char *in, char *chain)
1854: {
1855: /* Substract chain 'chain' from 'in', return and output 'out' */
1.349 brouard 1856: /* in="V1+V1*age+age*age+V2", chain="+age*age" out="V1+V1*age+V2" */
1.187 brouard 1857:
1858: char *strloc;
1859:
1.349 brouard 1860: strcpy (out, in); /* out="V1+V1*age+age*age+V2" */
1861: strloc = strstr(out, chain); /* strloc points to out at "+age*age+V2" */
1862: printf("Bef strloc=%s chain=%s out=%s \n", strloc, chain, out); /* strloc=+age*age+V2 chain="+age*age", out="V1+V1*age+age*age+V2" */
1.187 brouard 1863: if(strloc != NULL){
1.349 brouard 1864: /* will affect out */ /* strloc+strlen(chain)=|+V2 = "V1+V1*age+age*age|+V2" */ /* Will also work in Unicodek */
1865: memmove(strloc,strloc+strlen(chain), strlen(strloc+strlen(chain))+1); /* move number of bytes corresponding to the length of "+V2" which is 3, plus one is 4 (including the null)*/
1866: /* equivalent to strcpy (strloc, strloc +strlen(chain)) if no overlap; Copies from "+V2" to V1+V1*age+ */
1.187 brouard 1867: }
1.349 brouard 1868: printf("Aft strloc=%s chain=%s in=%s out=%s \n", strloc, chain, in, out); /* strloc=+V2 chain="+age*age", in="V1+V1*age+age*age+V2", out="V1+V1*age+V2" */
1.187 brouard 1869: return out;
1870: }
1871:
1872:
1.145 brouard 1873: char *cutl(char *blocc, char *alocc, char *in, char occ)
1874: {
1.187 brouard 1875: /* cuts string in into blocc and alocc where blocc ends before FIRST occurence of char 'occ'
1.349 brouard 1876: and alocc starts after first occurence of char 'occ' : ex cutl(blocc,alocc,"abcdef2ghi2j",'2')
1.310 brouard 1877: gives alocc="abcdef" and blocc="ghi2j".
1.145 brouard 1878: If occ is not found blocc is null and alocc is equal to in. Returns blocc
1879: */
1.160 brouard 1880: char *s, *t;
1.145 brouard 1881: t=in;s=in;
1882: while ((*in != occ) && (*in != '\0')){
1883: *alocc++ = *in++;
1884: }
1885: if( *in == occ){
1886: *(alocc)='\0';
1887: s=++in;
1888: }
1889:
1890: if (s == t) {/* occ not found */
1891: *(alocc-(in-s))='\0';
1892: in=s;
1893: }
1894: while ( *in != '\0'){
1895: *blocc++ = *in++;
1896: }
1897:
1898: *blocc='\0';
1899: return t;
1900: }
1.137 brouard 1901: char *cutv(char *blocc, char *alocc, char *in, char occ)
1902: {
1.187 brouard 1903: /* cuts string in into blocc and alocc where blocc ends before LAST occurence of char 'occ'
1.137 brouard 1904: and alocc starts after last occurence of char 'occ' : ex cutv(blocc,alocc,"abcdef2ghi2j",'2')
1905: gives blocc="abcdef2ghi" and alocc="j".
1906: If occ is not found blocc is null and alocc is equal to in. Returns alocc
1907: */
1908: char *s, *t;
1909: t=in;s=in;
1910: while (*in != '\0'){
1911: while( *in == occ){
1912: *blocc++ = *in++;
1913: s=in;
1914: }
1915: *blocc++ = *in++;
1916: }
1917: if (s == t) /* occ not found */
1918: *(blocc-(in-s))='\0';
1919: else
1920: *(blocc-(in-s)-1)='\0';
1921: in=s;
1922: while ( *in != '\0'){
1923: *alocc++ = *in++;
1924: }
1925:
1926: *alocc='\0';
1927: return s;
1928: }
1929:
1.126 brouard 1930: int nbocc(char *s, char occ)
1931: {
1932: int i,j=0;
1933: int lg=20;
1934: i=0;
1935: lg=strlen(s);
1936: for(i=0; i<= lg; i++) {
1.234 brouard 1937: if (s[i] == occ ) j++;
1.126 brouard 1938: }
1939: return j;
1940: }
1941:
1.349 brouard 1942: int nboccstr(char *textin, char *chain)
1943: {
1944: /* Counts the number of occurence of "chain" in string textin */
1945: /* in="+V7*V4+age*V2+age*V3+age*V4" chain="age" */
1946: char *strloc;
1947:
1948: int i,j=0;
1949:
1950: i=0;
1951:
1952: strloc=textin; /* strloc points to "^+V7*V4+age+..." in textin */
1953: for(;;) {
1954: strloc= strstr(strloc,chain); /* strloc points to first character of chain in textin if found. Example strloc points^ to "+V7*V4+^age" in textin */
1955: if(strloc != NULL){
1956: strloc = strloc+strlen(chain); /* strloc points to "+V7*V4+age^" in textin */
1957: j++;
1958: }else
1959: break;
1960: }
1961: return j;
1962:
1963: }
1.137 brouard 1964: /* void cutv(char *u,char *v, char*t, char occ) */
1965: /* { */
1966: /* /\* cuts string t into u and v where u ends before last occurence of char 'occ' */
1967: /* and v starts after last occurence of char 'occ' : ex cutv(u,v,"abcdef2ghi2j",'2') */
1968: /* gives u="abcdef2ghi" and v="j" *\/ */
1969: /* int i,lg,j,p=0; */
1970: /* i=0; */
1971: /* lg=strlen(t); */
1972: /* for(j=0; j<=lg-1; j++) { */
1973: /* if((t[j]!= occ) && (t[j+1]== occ)) p=j+1; */
1974: /* } */
1.126 brouard 1975:
1.137 brouard 1976: /* for(j=0; j<p; j++) { */
1977: /* (u[j] = t[j]); */
1978: /* } */
1979: /* u[p]='\0'; */
1.126 brouard 1980:
1.137 brouard 1981: /* for(j=0; j<= lg; j++) { */
1982: /* if (j>=(p+1))(v[j-p-1] = t[j]); */
1983: /* } */
1984: /* } */
1.126 brouard 1985:
1.160 brouard 1986: #ifdef _WIN32
1987: char * strsep(char **pp, const char *delim)
1988: {
1989: char *p, *q;
1990:
1991: if ((p = *pp) == NULL)
1992: return 0;
1993: if ((q = strpbrk (p, delim)) != NULL)
1994: {
1995: *pp = q + 1;
1996: *q = '\0';
1997: }
1998: else
1999: *pp = 0;
2000: return p;
2001: }
2002: #endif
2003:
1.126 brouard 2004: /********************** nrerror ********************/
2005:
2006: void nrerror(char error_text[])
2007: {
2008: fprintf(stderr,"ERREUR ...\n");
2009: fprintf(stderr,"%s\n",error_text);
2010: exit(EXIT_FAILURE);
2011: }
2012: /*********************** vector *******************/
2013: double *vector(int nl, int nh)
2014: {
2015: double *v;
2016: v=(double *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(double)));
2017: if (!v) nrerror("allocation failure in vector");
2018: return v-nl+NR_END;
2019: }
2020:
2021: /************************ free vector ******************/
2022: void free_vector(double*v, int nl, int nh)
2023: {
2024: free((FREE_ARG)(v+nl-NR_END));
2025: }
2026:
2027: /************************ivector *******************************/
2028: int *ivector(long nl,long nh)
2029: {
2030: int *v;
2031: v=(int *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(int)));
2032: if (!v) nrerror("allocation failure in ivector");
2033: return v-nl+NR_END;
2034: }
2035:
2036: /******************free ivector **************************/
2037: void free_ivector(int *v, long nl, long nh)
2038: {
2039: free((FREE_ARG)(v+nl-NR_END));
2040: }
2041:
2042: /************************lvector *******************************/
2043: long *lvector(long nl,long nh)
2044: {
2045: long *v;
2046: v=(long *) malloc((size_t)((nh-nl+1+NR_END)*sizeof(long)));
2047: if (!v) nrerror("allocation failure in ivector");
2048: return v-nl+NR_END;
2049: }
2050:
2051: /******************free lvector **************************/
2052: void free_lvector(long *v, long nl, long nh)
2053: {
2054: free((FREE_ARG)(v+nl-NR_END));
2055: }
2056:
2057: /******************* imatrix *******************************/
2058: int **imatrix(long nrl, long nrh, long ncl, long nch)
2059: /* allocate a int matrix with subscript range m[nrl..nrh][ncl..nch] */
2060: {
2061: long i, nrow=nrh-nrl+1,ncol=nch-ncl+1;
2062: int **m;
2063:
2064: /* allocate pointers to rows */
2065: m=(int **) malloc((size_t)((nrow+NR_END)*sizeof(int*)));
2066: if (!m) nrerror("allocation failure 1 in matrix()");
2067: m += NR_END;
2068: m -= nrl;
2069:
2070:
2071: /* allocate rows and set pointers to them */
2072: m[nrl]=(int *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(int)));
2073: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2074: m[nrl] += NR_END;
2075: m[nrl] -= ncl;
2076:
2077: for(i=nrl+1;i<=nrh;i++) m[i]=m[i-1]+ncol;
2078:
2079: /* return pointer to array of pointers to rows */
2080: return m;
2081: }
2082:
2083: /****************** free_imatrix *************************/
2084: void free_imatrix(m,nrl,nrh,ncl,nch)
2085: int **m;
2086: long nch,ncl,nrh,nrl;
2087: /* free an int matrix allocated by imatrix() */
2088: {
2089: free((FREE_ARG) (m[nrl]+ncl-NR_END));
2090: free((FREE_ARG) (m+nrl-NR_END));
2091: }
2092:
2093: /******************* matrix *******************************/
2094: double **matrix(long nrl, long nrh, long ncl, long nch)
2095: {
2096: long i, nrow=nrh-nrl+1, ncol=nch-ncl+1;
2097: double **m;
2098:
2099: m=(double **) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2100: if (!m) nrerror("allocation failure 1 in matrix()");
2101: m += NR_END;
2102: m -= nrl;
2103:
2104: m[nrl]=(double *) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2105: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2106: m[nrl] += NR_END;
2107: m[nrl] -= ncl;
2108:
2109: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2110: return m;
1.145 brouard 2111: /* print *(*(m+1)+70) or print m[1][70]; print m+1 or print &(m[1]) or &(m[1][0])
2112: m[i] = address of ith row of the table. &(m[i]) is its value which is another adress
2113: that of m[i][0]. In order to get the value p m[i][0] but it is unitialized.
1.126 brouard 2114: */
2115: }
2116:
2117: /*************************free matrix ************************/
2118: void free_matrix(double **m, long nrl, long nrh, long ncl, long nch)
2119: {
2120: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2121: free((FREE_ARG)(m+nrl-NR_END));
2122: }
2123:
2124: /******************* ma3x *******************************/
2125: double ***ma3x(long nrl, long nrh, long ncl, long nch, long nll, long nlh)
2126: {
2127: long i, j, nrow=nrh-nrl+1, ncol=nch-ncl+1, nlay=nlh-nll+1;
2128: double ***m;
2129:
2130: m=(double ***) malloc((size_t)((nrow+NR_END)*sizeof(double*)));
2131: if (!m) nrerror("allocation failure 1 in matrix()");
2132: m += NR_END;
2133: m -= nrl;
2134:
2135: m[nrl]=(double **) malloc((size_t)((nrow*ncol+NR_END)*sizeof(double)));
2136: if (!m[nrl]) nrerror("allocation failure 2 in matrix()");
2137: m[nrl] += NR_END;
2138: m[nrl] -= ncl;
2139:
2140: for (i=nrl+1; i<=nrh; i++) m[i]=m[i-1]+ncol;
2141:
2142: m[nrl][ncl]=(double *) malloc((size_t)((nrow*ncol*nlay+NR_END)*sizeof(double)));
2143: if (!m[nrl][ncl]) nrerror("allocation failure 3 in matrix()");
2144: m[nrl][ncl] += NR_END;
2145: m[nrl][ncl] -= nll;
2146: for (j=ncl+1; j<=nch; j++)
2147: m[nrl][j]=m[nrl][j-1]+nlay;
2148:
2149: for (i=nrl+1; i<=nrh; i++) {
2150: m[i][ncl]=m[i-1l][ncl]+ncol*nlay;
2151: for (j=ncl+1; j<=nch; j++)
2152: m[i][j]=m[i][j-1]+nlay;
2153: }
2154: return m;
2155: /* gdb: p *(m+1) <=> p m[1] and p (m+1) <=> p (m+1) <=> p &(m[1])
2156: &(m[i][j][k]) <=> *((*(m+i) + j)+k)
2157: */
2158: }
2159:
2160: /*************************free ma3x ************************/
2161: void free_ma3x(double ***m, long nrl, long nrh, long ncl, long nch,long nll, long nlh)
2162: {
2163: free((FREE_ARG)(m[nrl][ncl]+ nll-NR_END));
2164: free((FREE_ARG)(m[nrl]+ncl-NR_END));
2165: free((FREE_ARG)(m+nrl-NR_END));
2166: }
2167:
2168: /*************** function subdirf ***********/
2169: char *subdirf(char fileres[])
2170: {
2171: /* Caution optionfilefiname is hidden */
2172: strcpy(tmpout,optionfilefiname);
2173: strcat(tmpout,"/"); /* Add to the right */
2174: strcat(tmpout,fileres);
2175: return tmpout;
2176: }
2177:
2178: /*************** function subdirf2 ***********/
2179: char *subdirf2(char fileres[], char *preop)
2180: {
1.314 brouard 2181: /* Example subdirf2(optionfilefiname,"FB_") with optionfilefiname="texte", result="texte/FB_texte"
2182: Errors in subdirf, 2, 3 while printing tmpout is
1.315 brouard 2183: rewritten within the same printf. Workaround: many printfs */
1.126 brouard 2184: /* Caution optionfilefiname is hidden */
2185: strcpy(tmpout,optionfilefiname);
2186: strcat(tmpout,"/");
2187: strcat(tmpout,preop);
2188: strcat(tmpout,fileres);
2189: return tmpout;
2190: }
2191:
2192: /*************** function subdirf3 ***********/
2193: char *subdirf3(char fileres[], char *preop, char *preop2)
2194: {
2195:
2196: /* Caution optionfilefiname is hidden */
2197: strcpy(tmpout,optionfilefiname);
2198: strcat(tmpout,"/");
2199: strcat(tmpout,preop);
2200: strcat(tmpout,preop2);
2201: strcat(tmpout,fileres);
2202: return tmpout;
2203: }
1.213 brouard 2204:
2205: /*************** function subdirfext ***********/
2206: char *subdirfext(char fileres[], char *preop, char *postop)
2207: {
2208:
2209: strcpy(tmpout,preop);
2210: strcat(tmpout,fileres);
2211: strcat(tmpout,postop);
2212: return tmpout;
2213: }
1.126 brouard 2214:
1.213 brouard 2215: /*************** function subdirfext3 ***********/
2216: char *subdirfext3(char fileres[], char *preop, char *postop)
2217: {
2218:
2219: /* Caution optionfilefiname is hidden */
2220: strcpy(tmpout,optionfilefiname);
2221: strcat(tmpout,"/");
2222: strcat(tmpout,preop);
2223: strcat(tmpout,fileres);
2224: strcat(tmpout,postop);
2225: return tmpout;
2226: }
2227:
1.162 brouard 2228: char *asc_diff_time(long time_sec, char ascdiff[])
2229: {
2230: long sec_left, days, hours, minutes;
2231: days = (time_sec) / (60*60*24);
2232: sec_left = (time_sec) % (60*60*24);
2233: hours = (sec_left) / (60*60) ;
2234: sec_left = (sec_left) %(60*60);
2235: minutes = (sec_left) /60;
2236: sec_left = (sec_left) % (60);
2237: sprintf(ascdiff,"%ld day(s) %ld hour(s) %ld minute(s) %ld second(s)",days, hours, minutes, sec_left);
2238: return ascdiff;
2239: }
2240:
1.126 brouard 2241: /***************** f1dim *************************/
2242: extern int ncom;
2243: extern double *pcom,*xicom;
2244: extern double (*nrfunc)(double []);
2245:
2246: double f1dim(double x)
2247: {
2248: int j;
2249: double f;
2250: double *xt;
2251:
2252: xt=vector(1,ncom);
2253: for (j=1;j<=ncom;j++) xt[j]=pcom[j]+x*xicom[j];
2254: f=(*nrfunc)(xt);
2255: free_vector(xt,1,ncom);
2256: return f;
2257: }
2258:
2259: /*****************brent *************************/
2260: double brent(double ax, double bx, double cx, double (*f)(double), double tol, double *xmin)
1.187 brouard 2261: {
2262: /* Given a function f, and given a bracketing triplet of abscissas ax, bx, cx (such that bx is
2263: * between ax and cx, and f(bx) is less than both f(ax) and f(cx) ), this routine isolates
2264: * the minimum to a fractional precision of about tol using Brent’s method. The abscissa of
2265: * the minimum is returned as xmin, and the minimum function value is returned as brent , the
2266: * returned function value.
2267: */
1.126 brouard 2268: int iter;
2269: double a,b,d,etemp;
1.159 brouard 2270: double fu=0,fv,fw,fx;
1.164 brouard 2271: double ftemp=0.;
1.126 brouard 2272: double p,q,r,tol1,tol2,u,v,w,x,xm;
2273: double e=0.0;
2274:
2275: a=(ax < cx ? ax : cx);
2276: b=(ax > cx ? ax : cx);
2277: x=w=v=bx;
2278: fw=fv=fx=(*f)(x);
2279: for (iter=1;iter<=ITMAX;iter++) {
2280: xm=0.5*(a+b);
2281: tol2=2.0*(tol1=tol*fabs(x)+ZEPS);
2282: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret)))*/
2283: printf(".");fflush(stdout);
2284: fprintf(ficlog,".");fflush(ficlog);
1.162 brouard 2285: #ifdef DEBUGBRENT
1.126 brouard 2286: printf("br %d,x=%.10e xm=%.10e b=%.10e a=%.10e tol=%.10e tol1=%.10e tol2=%.10e x-xm=%.10e fx=%.12e fu=%.12e,fw=%.12e,ftemp=%.12e,ftol=%.12e\n",iter,x,xm,b,a,tol,tol1,tol2,(x-xm),fx,fu,fw,ftemp,ftol);
2287: fprintf(ficlog,"br %d,x=%.10e xm=%.10e b=%.10e a=%.10e tol=%.10e tol1=%.10e tol2=%.10e x-xm=%.10e fx=%.12e fu=%.12e,fw=%.12e,ftemp=%.12e,ftol=%.12e\n",iter,x,xm,b,a,tol,tol1,tol2,(x-xm),fx,fu,fw,ftemp,ftol);
2288: /* if ((fabs(x-xm) <= (tol2-0.5*(b-a)))||(2.0*fabs(fu-ftemp) <= ftol*1.e-2*(fabs(fu)+fabs(ftemp)))) { */
2289: #endif
2290: if (fabs(x-xm) <= (tol2-0.5*(b-a))){
2291: *xmin=x;
2292: return fx;
2293: }
2294: ftemp=fu;
2295: if (fabs(e) > tol1) {
2296: r=(x-w)*(fx-fv);
2297: q=(x-v)*(fx-fw);
2298: p=(x-v)*q-(x-w)*r;
2299: q=2.0*(q-r);
2300: if (q > 0.0) p = -p;
2301: q=fabs(q);
2302: etemp=e;
2303: e=d;
2304: if (fabs(p) >= fabs(0.5*q*etemp) || p <= q*(a-x) || p >= q*(b-x))
1.224 brouard 2305: d=CGOLD*(e=(x >= xm ? a-x : b-x));
1.126 brouard 2306: else {
1.224 brouard 2307: d=p/q;
2308: u=x+d;
2309: if (u-a < tol2 || b-u < tol2)
2310: d=SIGN(tol1,xm-x);
1.126 brouard 2311: }
2312: } else {
2313: d=CGOLD*(e=(x >= xm ? a-x : b-x));
2314: }
2315: u=(fabs(d) >= tol1 ? x+d : x+SIGN(tol1,d));
2316: fu=(*f)(u);
2317: if (fu <= fx) {
2318: if (u >= x) a=x; else b=x;
2319: SHFT(v,w,x,u)
1.183 brouard 2320: SHFT(fv,fw,fx,fu)
2321: } else {
2322: if (u < x) a=u; else b=u;
2323: if (fu <= fw || w == x) {
1.224 brouard 2324: v=w;
2325: w=u;
2326: fv=fw;
2327: fw=fu;
1.183 brouard 2328: } else if (fu <= fv || v == x || v == w) {
1.224 brouard 2329: v=u;
2330: fv=fu;
1.183 brouard 2331: }
2332: }
1.126 brouard 2333: }
2334: nrerror("Too many iterations in brent");
2335: *xmin=x;
2336: return fx;
2337: }
2338:
2339: /****************** mnbrak ***********************/
2340:
2341: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb, double *fc,
2342: double (*func)(double))
1.183 brouard 2343: { /* Given a function func , and given distinct initial points ax and bx , this routine searches in
2344: the downhill direction (defined by the function as evaluated at the initial points) and returns
2345: new points ax , bx , cx that bracket a minimum of the function. Also returned are the function
2346: values at the three points, fa, fb , and fc such that fa > fb and fb < fc.
2347: */
1.126 brouard 2348: double ulim,u,r,q, dum;
2349: double fu;
1.187 brouard 2350:
2351: double scale=10.;
2352: int iterscale=0;
2353:
2354: *fa=(*func)(*ax); /* xta[j]=pcom[j]+(*ax)*xicom[j]; fa=f(xta[j])*/
2355: *fb=(*func)(*bx); /* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) */
2356:
2357:
2358: /* while(*fb != *fb){ /\* *ax should be ok, reducing distance to *ax *\/ */
2359: /* printf("Warning mnbrak *fb = %lf, *bx=%lf *ax=%lf *fa==%lf iter=%d\n",*fb, *bx, *ax, *fa, iterscale++); */
2360: /* *bx = *ax - (*ax - *bx)/scale; */
2361: /* *fb=(*func)(*bx); /\* xtb[j]=pcom[j]+(*bx)*xicom[j]; fb=f(xtb[j]) *\/ */
2362: /* } */
2363:
1.126 brouard 2364: if (*fb > *fa) {
2365: SHFT(dum,*ax,*bx,dum)
1.183 brouard 2366: SHFT(dum,*fb,*fa,dum)
2367: }
1.126 brouard 2368: *cx=(*bx)+GOLD*(*bx-*ax);
2369: *fc=(*func)(*cx);
1.183 brouard 2370: #ifdef DEBUG
1.224 brouard 2371: printf("mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
2372: fprintf(ficlog,"mnbrak0 a=%lf *fa=%lf, b=%lf *fb=%lf, c=%lf *fc=%lf\n",*ax,*fa,*bx,*fb,*cx, *fc);
1.183 brouard 2373: #endif
1.224 brouard 2374: while (*fb > *fc) { /* Declining a,b,c with fa> fb > fc. If fc=inf it exits and if flat fb=fc it exits too.*/
1.126 brouard 2375: r=(*bx-*ax)*(*fb-*fc);
1.224 brouard 2376: q=(*bx-*cx)*(*fb-*fa); /* What if fa=inf */
1.126 brouard 2377: u=(*bx)-((*bx-*cx)*q-(*bx-*ax)*r)/
1.183 brouard 2378: (2.0*SIGN(FMAX(fabs(q-r),TINY),q-r)); /* Minimum abscissa of a parabolic estimated from (a,fa), (b,fb) and (c,fc). */
2379: ulim=(*bx)+GLIMIT*(*cx-*bx); /* Maximum abscissa where function should be evaluated */
2380: if ((*bx-u)*(u-*cx) > 0.0) { /* if u_p is between b and c */
1.126 brouard 2381: fu=(*func)(u);
1.163 brouard 2382: #ifdef DEBUG
2383: /* f(x)=A(x-u)**2+f(u) */
2384: double A, fparabu;
2385: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2386: fparabu= *fa - A*(*ax-u)*(*ax-u);
1.224 brouard 2387: printf("\nmnbrak (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf), (*u=%.12f, fu=%.12lf, fparabu=%.12f, q=%lf < %lf=r)\n",*ax,*fa,*bx,*fb,*cx,*fc,u,fu, fparabu,q,r);
2388: fprintf(ficlog,"\nmnbrak (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf), (*u=%.12f, fu=%.12lf, fparabu=%.12f, q=%lf < %lf=r)\n",*ax,*fa,*bx,*fb,*cx,*fc,u,fu, fparabu,q,r);
1.183 brouard 2389: /* And thus,it can be that fu > *fc even if fparabu < *fc */
2390: /* mnbrak (*ax=7.666299858533, *fa=299039.693133272231), (*bx=8.595447774979, *fb=298976.598289369489),
2391: (*cx=10.098840694817, *fc=298946.631474258087), (*u=9.852501168332, fu=298948.773013752128, fparabu=298945.434711494134) */
2392: /* In that case, there is no bracket in the output! Routine is wrong with many consequences.*/
1.163 brouard 2393: #endif
1.184 brouard 2394: #ifdef MNBRAKORIGINAL
1.183 brouard 2395: #else
1.191 brouard 2396: /* if (fu > *fc) { */
2397: /* #ifdef DEBUG */
2398: /* printf("mnbrak4 fu > fc \n"); */
2399: /* fprintf(ficlog, "mnbrak4 fu > fc\n"); */
2400: /* #endif */
2401: /* /\* SHFT(u,*cx,*cx,u) /\\* ie a=c, c=u and u=c; in that case, next SHFT(a,b,c,u) will give a=b=b, b=c=u, c=u=c and *\\/ *\/ */
2402: /* /\* SHFT(*fa,*fc,fu,*fc) /\\* (b, u, c) is a bracket while test fb > fc will be fu > fc will exit *\\/ *\/ */
2403: /* dum=u; /\* Shifting c and u *\/ */
2404: /* u = *cx; */
2405: /* *cx = dum; */
2406: /* dum = fu; */
2407: /* fu = *fc; */
2408: /* *fc =dum; */
2409: /* } else { /\* end *\/ */
2410: /* #ifdef DEBUG */
2411: /* printf("mnbrak3 fu < fc \n"); */
2412: /* fprintf(ficlog, "mnbrak3 fu < fc\n"); */
2413: /* #endif */
2414: /* dum=u; /\* Shifting c and u *\/ */
2415: /* u = *cx; */
2416: /* *cx = dum; */
2417: /* dum = fu; */
2418: /* fu = *fc; */
2419: /* *fc =dum; */
2420: /* } */
1.224 brouard 2421: #ifdef DEBUGMNBRAK
2422: double A, fparabu;
2423: A= (*fb - *fa)/(*bx-*ax)/(*bx+*ax-2*u);
2424: fparabu= *fa - A*(*ax-u)*(*ax-u);
2425: printf("\nmnbrak35 ax=%lf fa=%lf bx=%lf fb=%lf, u=%lf fp=%lf fu=%lf < or >= fc=%lf cx=%lf, q=%lf < %lf=r \n",*ax, *fa, *bx,*fb,u,fparabu,fu,*fc,*cx,q,r);
2426: fprintf(ficlog,"\nmnbrak35 ax=%lf fa=%lf bx=%lf fb=%lf, u=%lf fp=%lf fu=%lf < or >= fc=%lf cx=%lf, q=%lf < %lf=r \n",*ax, *fa, *bx,*fb,u,fparabu,fu,*fc,*cx,q,r);
1.183 brouard 2427: #endif
1.191 brouard 2428: dum=u; /* Shifting c and u */
2429: u = *cx;
2430: *cx = dum;
2431: dum = fu;
2432: fu = *fc;
2433: *fc =dum;
1.183 brouard 2434: #endif
1.162 brouard 2435: } else if ((*cx-u)*(u-ulim) > 0.0) { /* u is after c but before ulim */
1.183 brouard 2436: #ifdef DEBUG
1.224 brouard 2437: printf("\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
2438: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim\n",u,*cx);
1.183 brouard 2439: #endif
1.126 brouard 2440: fu=(*func)(u);
2441: if (fu < *fc) {
1.183 brouard 2442: #ifdef DEBUG
1.224 brouard 2443: printf("\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2444: fprintf(ficlog,"\nmnbrak2 u=%lf after c=%lf but before ulim=%lf AND fu=%lf < %lf=fc\n",u,*cx,ulim,fu, *fc);
2445: #endif
2446: SHFT(*bx,*cx,u,*cx+GOLD*(*cx-*bx))
2447: SHFT(*fb,*fc,fu,(*func)(u))
2448: #ifdef DEBUG
2449: printf("\nmnbrak2 shift GOLD c=%lf",*cx+GOLD*(*cx-*bx));
1.183 brouard 2450: #endif
2451: }
1.162 brouard 2452: } else if ((u-ulim)*(ulim-*cx) >= 0.0) { /* u outside ulim (verifying that ulim is beyond c) */
1.183 brouard 2453: #ifdef DEBUG
1.224 brouard 2454: printf("\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
2455: fprintf(ficlog,"\nmnbrak2 u=%lf outside ulim=%lf (verifying that ulim is beyond c=%lf)\n",u,ulim,*cx);
1.183 brouard 2456: #endif
1.126 brouard 2457: u=ulim;
2458: fu=(*func)(u);
1.183 brouard 2459: } else { /* u could be left to b (if r > q parabola has a maximum) */
2460: #ifdef DEBUG
1.224 brouard 2461: printf("\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
2462: fprintf(ficlog,"\nmnbrak2 u=%lf could be left to b=%lf (if r=%lf > q=%lf parabola has a maximum)\n",u,*bx,r,q);
1.183 brouard 2463: #endif
1.126 brouard 2464: u=(*cx)+GOLD*(*cx-*bx);
2465: fu=(*func)(u);
1.224 brouard 2466: #ifdef DEBUG
2467: printf("\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2468: fprintf(ficlog,"\nmnbrak2 new u=%lf fu=%lf shifted gold left from c=%lf and b=%lf \n",u,fu,*cx,*bx);
2469: #endif
1.183 brouard 2470: } /* end tests */
1.126 brouard 2471: SHFT(*ax,*bx,*cx,u)
1.183 brouard 2472: SHFT(*fa,*fb,*fc,fu)
2473: #ifdef DEBUG
1.224 brouard 2474: printf("\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
2475: fprintf(ficlog, "\nmnbrak2 shift (*ax=%.12f, *fa=%.12lf), (*bx=%.12f, *fb=%.12lf), (*cx=%.12f, *fc=%.12lf)\n",*ax,*fa,*bx,*fb,*cx,*fc);
1.183 brouard 2476: #endif
2477: } /* end while; ie return (a, b, c, fa, fb, fc) such that a < b < c with f(a) > f(b) and fb < f(c) */
1.126 brouard 2478: }
2479:
2480: /*************** linmin ************************/
1.162 brouard 2481: /* Given an n -dimensional point p[1..n] and an n -dimensional direction xi[1..n] , moves and
2482: resets p to where the function func(p) takes on a minimum along the direction xi from p ,
2483: and replaces xi by the actual vector displacement that p was moved. Also returns as fret
2484: the value of func at the returned location p . This is actually all accomplished by calling the
2485: routines mnbrak and brent .*/
1.126 brouard 2486: int ncom;
2487: double *pcom,*xicom;
2488: double (*nrfunc)(double []);
2489:
1.224 brouard 2490: #ifdef LINMINORIGINAL
1.126 brouard 2491: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []))
1.224 brouard 2492: #else
2493: void linmin(double p[], double xi[], int n, double *fret,double (*func)(double []), int *flat)
2494: #endif
1.126 brouard 2495: {
2496: double brent(double ax, double bx, double cx,
2497: double (*f)(double), double tol, double *xmin);
2498: double f1dim(double x);
2499: void mnbrak(double *ax, double *bx, double *cx, double *fa, double *fb,
2500: double *fc, double (*func)(double));
2501: int j;
2502: double xx,xmin,bx,ax;
2503: double fx,fb,fa;
1.187 brouard 2504:
1.203 brouard 2505: #ifdef LINMINORIGINAL
2506: #else
2507: double scale=10., axs, xxs; /* Scale added for infinity */
2508: #endif
2509:
1.126 brouard 2510: ncom=n;
2511: pcom=vector(1,n);
2512: xicom=vector(1,n);
2513: nrfunc=func;
2514: for (j=1;j<=n;j++) {
2515: pcom[j]=p[j];
1.202 brouard 2516: xicom[j]=xi[j]; /* Former scale xi[j] of currrent direction i */
1.126 brouard 2517: }
1.187 brouard 2518:
1.203 brouard 2519: #ifdef LINMINORIGINAL
2520: xx=1.;
2521: #else
2522: axs=0.0;
2523: xxs=1.;
2524: do{
2525: xx= xxs;
2526: #endif
1.187 brouard 2527: ax=0.;
2528: mnbrak(&ax,&xx,&bx,&fa,&fx,&fb,f1dim); /* Outputs: xtx[j]=pcom[j]+(*xx)*xicom[j]; fx=f(xtx[j]) */
2529: /* brackets with inputs ax=0 and xx=1, but points, pcom=p, and directions values, xicom=xi, are sent via f1dim(x) */
2530: /* xt[x,j]=pcom[j]+x*xicom[j] f(ax) = f(xt(a,j=1,n)) = f(p(j) + 0 * xi(j)) and f(xx) = f(xt(x, j=1,n)) = f(p(j) + 1 * xi(j)) */
2531: /* Outputs: fa=f(p(j)) and fx=f(p(j) + xxs * xi(j) ) and f(bx)= f(p(j)+ bx* xi(j)) */
2532: /* Given input ax=axs and xx=xxs, xx might be too far from ax to get a finite f(xx) */
2533: /* Searches on line, outputs (ax, xx, bx) such that fx < min(fa and fb) */
2534: /* Find a bracket a,x,b in direction n=xi ie xicom, order may change. Scale is [0:xxs*xi[j]] et non plus [0:xi[j]]*/
1.203 brouard 2535: #ifdef LINMINORIGINAL
2536: #else
2537: if (fx != fx){
1.224 brouard 2538: xxs=xxs/scale; /* Trying a smaller xx, closer to initial ax=0 */
2539: printf("|");
2540: fprintf(ficlog,"|");
1.203 brouard 2541: #ifdef DEBUGLINMIN
1.224 brouard 2542: printf("\nLinmin NAN : input [axs=%lf:xxs=%lf], mnbrak outputs fx=%lf <(fb=%lf and fa=%lf) with xx=%lf in [ax=%lf:bx=%lf] \n", axs, xxs, fx,fb, fa, xx, ax, bx);
1.203 brouard 2543: #endif
2544: }
1.224 brouard 2545: }while(fx != fx && xxs > 1.e-5);
1.203 brouard 2546: #endif
2547:
1.191 brouard 2548: #ifdef DEBUGLINMIN
2549: printf("\nLinmin after mnbrak: ax=%12.7f xx=%12.7f bx=%12.7f fa=%12.2f fx=%12.2f fb=%12.2f\n", ax,xx,bx,fa,fx,fb);
1.202 brouard 2550: fprintf(ficlog,"\nLinmin after mnbrak: ax=%12.7f xx=%12.7f bx=%12.7f fa=%12.2f fx=%12.2f fb=%12.2f\n", ax,xx,bx,fa,fx,fb);
1.191 brouard 2551: #endif
1.224 brouard 2552: #ifdef LINMINORIGINAL
2553: #else
1.317 brouard 2554: if(fb == fx){ /* Flat function in the direction */
2555: xmin=xx;
1.224 brouard 2556: *flat=1;
1.317 brouard 2557: }else{
1.224 brouard 2558: *flat=0;
2559: #endif
2560: /*Flat mnbrak2 shift (*ax=0.000000000000, *fa=51626.272983130431), (*bx=-1.618034000000, *fb=51590.149499362531), (*cx=-4.236068025156, *fc=51590.149499362531) */
1.187 brouard 2561: *fret=brent(ax,xx,bx,f1dim,TOL,&xmin); /* Giving a bracketting triplet (ax, xx, bx), find a minimum, xmin, according to f1dim, *fret(xmin),*/
2562: /* fa = f(p[j] + ax * xi[j]), fx = f(p[j] + xx * xi[j]), fb = f(p[j] + bx * xi[j]) */
2563: /* fmin = f(p[j] + xmin * xi[j]) */
2564: /* P+lambda n in that direction (lambdamin), with TOL between abscisses */
2565: /* f1dim(xmin): for (j=1;j<=ncom;j++) xt[j]=pcom[j]+xmin*xicom[j]; */
1.126 brouard 2566: #ifdef DEBUG
1.224 brouard 2567: printf("retour brent from bracket (a=%lf fa=%lf, xx=%lf fx=%lf, b=%lf fb=%lf): fret=%lf xmin=%lf\n",ax,fa,xx,fx,bx,fb,*fret,xmin);
2568: fprintf(ficlog,"retour brent from bracket (a=%lf fa=%lf, xx=%lf fx=%lf, b=%lf fb=%lf): fret=%lf xmin=%lf\n",ax,fa,xx,fx,bx,fb,*fret,xmin);
2569: #endif
2570: #ifdef LINMINORIGINAL
2571: #else
2572: }
1.126 brouard 2573: #endif
1.191 brouard 2574: #ifdef DEBUGLINMIN
2575: printf("linmin end ");
1.202 brouard 2576: fprintf(ficlog,"linmin end ");
1.191 brouard 2577: #endif
1.126 brouard 2578: for (j=1;j<=n;j++) {
1.203 brouard 2579: #ifdef LINMINORIGINAL
2580: xi[j] *= xmin;
2581: #else
2582: #ifdef DEBUGLINMIN
2583: if(xxs <1.0)
2584: printf(" before xi[%d]=%12.8f", j,xi[j]);
2585: #endif
2586: xi[j] *= xmin*xxs; /* xi rescaled by xmin and number of loops: if xmin=-1.237 and xi=(1,0,...,0) xi=(-1.237,0,...,0) */
2587: #ifdef DEBUGLINMIN
2588: if(xxs <1.0)
2589: printf(" after xi[%d]=%12.8f, xmin=%12.8f, ax=%12.8f, xx=%12.8f, bx=%12.8f, xxs=%12.8f", j,xi[j], xmin, ax, xx, bx,xxs );
2590: #endif
2591: #endif
1.187 brouard 2592: p[j] += xi[j]; /* Parameters values are updated accordingly */
1.126 brouard 2593: }
1.191 brouard 2594: #ifdef DEBUGLINMIN
1.203 brouard 2595: printf("\n");
1.191 brouard 2596: printf("Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.202 brouard 2597: fprintf(ficlog,"Comparing last *frec(xmin=%12.8f)=%12.8f from Brent and frec(0.)=%12.8f \n", xmin, *fret, (*func)(p));
1.191 brouard 2598: for (j=1;j<=n;j++) {
1.202 brouard 2599: printf(" xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2600: fprintf(ficlog," xi[%d]= %14.10f p[%d]= %12.7f",j,xi[j],j,p[j]);
2601: if(j % ncovmodel == 0){
1.191 brouard 2602: printf("\n");
1.202 brouard 2603: fprintf(ficlog,"\n");
2604: }
1.191 brouard 2605: }
1.203 brouard 2606: #else
1.191 brouard 2607: #endif
1.126 brouard 2608: free_vector(xicom,1,n);
2609: free_vector(pcom,1,n);
2610: }
2611:
2612:
2613: /*************** powell ************************/
1.162 brouard 2614: /*
1.317 brouard 2615: Minimization of a function func of n variables. Input consists in an initial starting point
2616: p[1..n] ; an initial matrix xi[1..n][1..n] whose columns contain the initial set of di-
2617: rections (usually the n unit vectors); and ftol, the fractional tolerance in the function value
2618: such that failure to decrease by more than this amount in one iteration signals doneness. On
1.162 brouard 2619: output, p is set to the best point found, xi is the then-current direction set, fret is the returned
2620: function value at p , and iter is the number of iterations taken. The routine linmin is used.
2621: */
1.224 brouard 2622: #ifdef LINMINORIGINAL
2623: #else
2624: int *flatdir; /* Function is vanishing in that direction */
1.225 brouard 2625: int flat=0, flatd=0; /* Function is vanishing in that direction */
1.224 brouard 2626: #endif
1.126 brouard 2627: void powell(double p[], double **xi, int n, double ftol, int *iter, double *fret,
2628: double (*func)(double []))
2629: {
1.224 brouard 2630: #ifdef LINMINORIGINAL
2631: void linmin(double p[], double xi[], int n, double *fret,
1.126 brouard 2632: double (*func)(double []));
1.224 brouard 2633: #else
1.241 brouard 2634: void linmin(double p[], double xi[], int n, double *fret,
2635: double (*func)(double []),int *flat);
1.224 brouard 2636: #endif
1.239 brouard 2637: int i,ibig,j,jk,k;
1.126 brouard 2638: double del,t,*pt,*ptt,*xit;
1.181 brouard 2639: double directest;
1.126 brouard 2640: double fp,fptt;
2641: double *xits;
2642: int niterf, itmp;
1.349 brouard 2643: int Bigter=0, nBigterf=1;
2644:
1.126 brouard 2645: pt=vector(1,n);
2646: ptt=vector(1,n);
2647: xit=vector(1,n);
2648: xits=vector(1,n);
2649: *fret=(*func)(p);
2650: for (j=1;j<=n;j++) pt[j]=p[j];
1.338 brouard 2651: rcurr_time = time(NULL);
2652: fp=(*fret); /* Initialisation */
1.126 brouard 2653: for (*iter=1;;++(*iter)) {
2654: ibig=0;
2655: del=0.0;
1.157 brouard 2656: rlast_time=rcurr_time;
1.349 brouard 2657: rlast_btime=rcurr_time;
1.157 brouard 2658: /* (void) gettimeofday(&curr_time,&tzp); */
2659: rcurr_time = time(NULL);
2660: curr_time = *localtime(&rcurr_time);
1.337 brouard 2661: /* printf("\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout); */
2662: /* fprintf(ficlog,"\nPowell iter=%d -2*LL=%.12f gain=%.12f=%.3g %ld sec. %ld sec.",*iter,*fret, fp-*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog); */
1.349 brouard 2663: Bigter=(*iter - *iter % ncovmodel)/ncovmodel +1; /* Big iteration, i.e on ncovmodel cycle */
2664: printf("\nPowell iter=%d Big Iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,Bigter,*fret,fp-*fret, rcurr_time-rlast_time, rcurr_time-rstart_time);fflush(stdout);
2665: fprintf(ficlog,"\nPowell iter=%d Big Iter=%d -2*LL=%.12f gain=%.3lg %ld sec. %ld sec.",*iter,Bigter,*fret,fp-*fret,rcurr_time-rlast_time, rcurr_time-rstart_time); fflush(ficlog);
2666: fprintf(ficrespow,"%d %d %.12f %d",*iter,Bigter, *fret,curr_time.tm_sec-start_time.tm_sec);
1.324 brouard 2667: fp=(*fret); /* From former iteration or initial value */
1.192 brouard 2668: for (i=1;i<=n;i++) {
1.126 brouard 2669: fprintf(ficrespow," %.12lf", p[i]);
2670: }
1.239 brouard 2671: fprintf(ficrespow,"\n");fflush(ficrespow);
2672: printf("\n#model= 1 + age ");
2673: fprintf(ficlog,"\n#model= 1 + age ");
2674: if(nagesqr==1){
1.241 brouard 2675: printf(" + age*age ");
2676: fprintf(ficlog," + age*age ");
1.239 brouard 2677: }
2678: for(j=1;j <=ncovmodel-2;j++){
2679: if(Typevar[j]==0) {
2680: printf(" + V%d ",Tvar[j]);
2681: fprintf(ficlog," + V%d ",Tvar[j]);
2682: }else if(Typevar[j]==1) {
2683: printf(" + V%d*age ",Tvar[j]);
2684: fprintf(ficlog," + V%d*age ",Tvar[j]);
2685: }else if(Typevar[j]==2) {
2686: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2687: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 2688: }else if(Typevar[j]==3) {
2689: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
2690: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.239 brouard 2691: }
2692: }
1.126 brouard 2693: printf("\n");
1.239 brouard 2694: /* printf("12 47.0114589 0.0154322 33.2424412 0.3279905 2.3731903 */
2695: /* 13 -21.5392400 0.1118147 1.2680506 1.2973408 -1.0663662 */
1.126 brouard 2696: fprintf(ficlog,"\n");
1.239 brouard 2697: for(i=1,jk=1; i <=nlstate; i++){
2698: for(k=1; k <=(nlstate+ndeath); k++){
2699: if (k != i) {
2700: printf("%d%d ",i,k);
2701: fprintf(ficlog,"%d%d ",i,k);
2702: for(j=1; j <=ncovmodel; j++){
2703: printf("%12.7f ",p[jk]);
2704: fprintf(ficlog,"%12.7f ",p[jk]);
2705: jk++;
2706: }
2707: printf("\n");
2708: fprintf(ficlog,"\n");
2709: }
2710: }
2711: }
1.241 brouard 2712: if(*iter <=3 && *iter >1){
1.157 brouard 2713: tml = *localtime(&rcurr_time);
2714: strcpy(strcurr,asctime(&tml));
2715: rforecast_time=rcurr_time;
1.126 brouard 2716: itmp = strlen(strcurr);
2717: if(strcurr[itmp-1]=='\n') /* Windows outputs with a new line */
1.241 brouard 2718: strcurr[itmp-1]='\0';
1.162 brouard 2719: printf("\nConsidering the time needed for the last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.157 brouard 2720: fprintf(ficlog,"\nConsidering the time needed for this last iteration #%d: %ld seconds,\n",*iter,rcurr_time-rlast_time);
1.349 brouard 2721: for(nBigterf=1;nBigterf<=31;nBigterf+=10){
2722: niterf=nBigterf*ncovmodel;
2723: /* rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time); */
1.241 brouard 2724: rforecast_time=rcurr_time+(niterf-*iter)*(rcurr_time-rlast_time);
2725: forecast_time = *localtime(&rforecast_time);
2726: strcpy(strfor,asctime(&forecast_time));
2727: itmp = strlen(strfor);
2728: if(strfor[itmp-1]=='\n')
2729: strfor[itmp-1]='\0';
1.349 brouard 2730: printf(" - if your program needs %d BIG iterations (%d iterations) to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",nBigterf, niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
2731: fprintf(ficlog," - if your program needs %d BIG iterations (%d iterations) to converge, convergence will be \n reached in %s i.e.\n on %s (current time is %s);\n",nBigterf, niterf, asc_diff_time(rforecast_time-rcurr_time,tmpout),strfor,strcurr);
1.126 brouard 2732: }
2733: }
1.187 brouard 2734: for (i=1;i<=n;i++) { /* For each direction i */
2735: for (j=1;j<=n;j++) xit[j]=xi[j][i]; /* Directions stored from previous iteration with previous scales */
1.126 brouard 2736: fptt=(*fret);
2737: #ifdef DEBUG
1.203 brouard 2738: printf("fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
2739: fprintf(ficlog, "fret=%lf, %lf, %lf \n", *fret, *fret, *fret);
1.126 brouard 2740: #endif
1.203 brouard 2741: printf("%d",i);fflush(stdout); /* print direction (parameter) i */
1.126 brouard 2742: fprintf(ficlog,"%d",i);fflush(ficlog);
1.224 brouard 2743: #ifdef LINMINORIGINAL
1.188 brouard 2744: linmin(p,xit,n,fret,func); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
1.224 brouard 2745: #else
2746: linmin(p,xit,n,fret,func,&flat); /* Point p[n]. xit[n] has been loaded for direction i as input.*/
2747: flatdir[i]=flat; /* Function is vanishing in that direction i */
2748: #endif
2749: /* Outputs are fret(new point p) p is updated and xit rescaled */
1.188 brouard 2750: if (fabs(fptt-(*fret)) > del) { /* We are keeping the max gain on each of the n directions */
1.224 brouard 2751: /* because that direction will be replaced unless the gain del is small */
2752: /* in comparison with the 'probable' gain, mu^2, with the last average direction. */
2753: /* Unless the n directions are conjugate some gain in the determinant may be obtained */
2754: /* with the new direction. */
2755: del=fabs(fptt-(*fret));
2756: ibig=i;
1.126 brouard 2757: }
2758: #ifdef DEBUG
2759: printf("%d %.12e",i,(*fret));
2760: fprintf(ficlog,"%d %.12e",i,(*fret));
2761: for (j=1;j<=n;j++) {
1.224 brouard 2762: xits[j]=FMAX(fabs(p[j]-pt[j]),1.e-5);
2763: printf(" x(%d)=%.12e",j,xit[j]);
2764: fprintf(ficlog," x(%d)=%.12e",j,xit[j]);
1.126 brouard 2765: }
2766: for(j=1;j<=n;j++) {
1.225 brouard 2767: printf(" p(%d)=%.12e",j,p[j]);
2768: fprintf(ficlog," p(%d)=%.12e",j,p[j]);
1.126 brouard 2769: }
2770: printf("\n");
2771: fprintf(ficlog,"\n");
2772: #endif
1.187 brouard 2773: } /* end loop on each direction i */
2774: /* Convergence test will use last linmin estimation (fret) and compare former iteration (fp) */
1.188 brouard 2775: /* But p and xit have been updated at the end of linmin, *fret corresponds to new p, xit */
1.187 brouard 2776: /* New value of last point Pn is not computed, P(n-1) */
1.319 brouard 2777: for(j=1;j<=n;j++) {
2778: if(flatdir[j] >0){
2779: printf(" p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
2780: fprintf(ficlog," p(%d)=%lf flat=%d ",j,p[j],flatdir[j]);
1.302 brouard 2781: }
1.319 brouard 2782: /* printf("\n"); */
2783: /* fprintf(ficlog,"\n"); */
2784: }
1.243 brouard 2785: /* if (2.0*fabs(fp-(*fret)) <= ftol*(fabs(fp)+fabs(*fret))) { /\* Did we reach enough precision? *\/ */
2786: if (2.0*fabs(fp-(*fret)) <= ftol) { /* Did we reach enough precision? */
1.188 brouard 2787: /* We could compare with a chi^2. chisquare(0.95,ddl=1)=3.84 */
2788: /* By adding age*age in a model, the new -2LL should be lower and the difference follows a */
2789: /* a chisquare statistics with 1 degree. To be significant at the 95% level, it should have */
2790: /* decreased of more than 3.84 */
2791: /* By adding age*age and V1*age the gain (-2LL) should be more than 5.99 (ddl=2) */
2792: /* By using V1+V2+V3, the gain should be 7.82, compared with basic 1+age. */
2793: /* By adding 10 parameters more the gain should be 18.31 */
1.224 brouard 2794:
1.188 brouard 2795: /* Starting the program with initial values given by a former maximization will simply change */
2796: /* the scales of the directions and the directions, because the are reset to canonical directions */
2797: /* Thus the first calls to linmin will give new points and better maximizations until fp-(*fret) is */
2798: /* under the tolerance value. If the tolerance is very small 1.e-9, it could last long. */
1.126 brouard 2799: #ifdef DEBUG
2800: int k[2],l;
2801: k[0]=1;
2802: k[1]=-1;
2803: printf("Max: %.12e",(*func)(p));
2804: fprintf(ficlog,"Max: %.12e",(*func)(p));
2805: for (j=1;j<=n;j++) {
2806: printf(" %.12e",p[j]);
2807: fprintf(ficlog," %.12e",p[j]);
2808: }
2809: printf("\n");
2810: fprintf(ficlog,"\n");
2811: for(l=0;l<=1;l++) {
2812: for (j=1;j<=n;j++) {
2813: ptt[j]=p[j]+(p[j]-pt[j])*k[l];
2814: printf("l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2815: fprintf(ficlog,"l=%d j=%d ptt=%.12e, xits=%.12e, p=%.12e, xit=%.12e", l,j,ptt[j],xits[j],p[j],xit[j]);
2816: }
2817: printf("func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2818: fprintf(ficlog,"func(ptt)=%.12e, deriv=%.12e\n",(*func)(ptt),(ptt[j]-p[j])/((*func)(ptt)-(*func)(p)));
2819: }
2820: #endif
2821:
2822: free_vector(xit,1,n);
2823: free_vector(xits,1,n);
2824: free_vector(ptt,1,n);
2825: free_vector(pt,1,n);
2826: return;
1.192 brouard 2827: } /* enough precision */
1.240 brouard 2828: if (*iter == ITMAX*n) nrerror("powell exceeding maximum iterations.");
1.181 brouard 2829: for (j=1;j<=n;j++) { /* Computes the extrapolated point P_0 + 2 (P_n-P_0) */
1.126 brouard 2830: ptt[j]=2.0*p[j]-pt[j];
2831: xit[j]=p[j]-pt[j];
2832: pt[j]=p[j];
2833: }
1.181 brouard 2834: fptt=(*func)(ptt); /* f_3 */
1.224 brouard 2835: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
2836: if (*iter <=4) {
1.225 brouard 2837: #else
2838: #endif
1.224 brouard 2839: #ifdef POWELLNOF3INFF1TEST /* skips test F3 <F1 */
1.192 brouard 2840: #else
1.161 brouard 2841: if (fptt < fp) { /* If extrapolated point is better, decide if we keep that new direction or not */
1.192 brouard 2842: #endif
1.162 brouard 2843: /* (x1 f1=fp), (x2 f2=*fret), (x3 f3=fptt), (xm fm) */
1.161 brouard 2844: /* From x1 (P0) distance of x2 is at h and x3 is 2h */
1.162 brouard 2845: /* Let f"(x2) be the 2nd derivative equal everywhere. */
2846: /* Then the parabolic through (x1,f1), (x2,f2) and (x3,f3) */
2847: /* will reach at f3 = fm + h^2/2 f"m ; f" = (f1 -2f2 +f3 ) / h**2 */
1.224 brouard 2848: /* Conditional for using this new direction is that mu^2 = (f1-2f2+f3)^2 /2 < del or directest <0 */
2849: /* also lamda^2=(f1-f2)^2/mu² is a parasite solution of powell */
2850: /* For powell, inclusion of this average direction is only if t(del)<0 or del inbetween mu^2 and lambda^2 */
1.161 brouard 2851: /* t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)-del*SQR(fp-fptt); */
1.224 brouard 2852: /* Even if f3 <f1, directest can be negative and t >0 */
2853: /* mu² and del² are equal when f3=f1 */
2854: /* f3 < f1 : mu² < del <= lambda^2 both test are equivalent */
2855: /* f3 < f1 : mu² < lambda^2 < del then directtest is negative and powell t is positive */
2856: /* f3 > f1 : lambda² < mu^2 < del then t is negative and directest >0 */
2857: /* f3 > f1 : lambda² < del < mu^2 then t is positive and directest >0 */
1.183 brouard 2858: #ifdef NRCORIGINAL
2859: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del)- del*SQR(fp-fptt); /* Original Numerical Recipes in C*/
2860: #else
2861: t=2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del); /* Intel compiler doesn't work on one line; bug reported */
1.161 brouard 2862: t= t- del*SQR(fp-fptt);
1.183 brouard 2863: #endif
1.202 brouard 2864: directest = fp-2.0*(*fret)+fptt - 2.0 * del; /* If delta was big enough we change it for a new direction */
1.161 brouard 2865: #ifdef DEBUG
1.181 brouard 2866: printf("t1= %.12lf, t2= %.12lf, t=%.12lf directest=%.12lf\n", 2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del),del*SQR(fp-fptt),t,directest);
2867: fprintf(ficlog,"t1= %.12lf, t2= %.12lf, t=%.12lf directest=%.12lf\n", 2.0*(fp-2.0*(*fret)+fptt)*SQR(fp-(*fret)-del),del*SQR(fp-fptt),t,directest);
1.161 brouard 2868: printf("t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2869: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2870: fprintf(ficlog,"t3= %.12lf, t4= %.12lf, t3*= %.12lf, t4*= %.12lf\n",SQR(fp-(*fret)-del),SQR(fp-fptt),
2871: (fp-(*fret)-del)*(fp-(*fret)-del),(fp-fptt)*(fp-fptt));
2872: printf("tt= %.12lf, t=%.12lf\n",2.0*(fp-2.0*(*fret)+fptt)*(fp-(*fret)-del)*(fp-(*fret)-del)-del*(fp-fptt)*(fp-fptt),t);
2873: fprintf(ficlog, "tt= %.12lf, t=%.12lf\n",2.0*(fp-2.0*(*fret)+fptt)*(fp-(*fret)-del)*(fp-(*fret)-del)-del*(fp-fptt)*(fp-fptt),t);
2874: #endif
1.183 brouard 2875: #ifdef POWELLORIGINAL
2876: if (t < 0.0) { /* Then we use it for new direction */
2877: #else
1.182 brouard 2878: if (directest*t < 0.0) { /* Contradiction between both tests */
1.224 brouard 2879: printf("directest= %.12lf (if <0 we include P0 Pn as new direction), t= %.12lf, f1= %.12lf,f2= %.12lf,f3= %.12lf, del= %.12lf\n",directest, t, fp,(*fret),fptt,del);
1.192 brouard 2880: printf("f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
1.224 brouard 2881: fprintf(ficlog,"directest= %.12lf (if directest<0 or t<0 we include P0 Pn as new direction), t= %.12lf, f1= %.12lf,f2= %.12lf,f3= %.12lf, del= %.12lf\n",directest, t, fp,(*fret),fptt, del);
1.192 brouard 2882: fprintf(ficlog,"f1-2f2+f3= %.12lf, f1-f2-del= %.12lf, f1-f3= %.12lf\n",fp-2.0*(*fret)+fptt, fp -(*fret) -del, fp-fptt);
2883: }
1.181 brouard 2884: if (directest < 0.0) { /* Then we use it for new direction */
2885: #endif
1.191 brouard 2886: #ifdef DEBUGLINMIN
1.234 brouard 2887: printf("Before linmin in direction P%d-P0\n",n);
2888: for (j=1;j<=n;j++) {
2889: printf(" Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2890: fprintf(ficlog," Before xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2891: if(j % ncovmodel == 0){
2892: printf("\n");
2893: fprintf(ficlog,"\n");
2894: }
2895: }
1.224 brouard 2896: #endif
2897: #ifdef LINMINORIGINAL
1.234 brouard 2898: linmin(p,xit,n,fret,func); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
1.224 brouard 2899: #else
1.234 brouard 2900: linmin(p,xit,n,fret,func,&flat); /* computes minimum on the extrapolated direction: changes p and rescales xit.*/
2901: flatdir[i]=flat; /* Function is vanishing in that direction i */
1.191 brouard 2902: #endif
1.234 brouard 2903:
1.191 brouard 2904: #ifdef DEBUGLINMIN
1.234 brouard 2905: for (j=1;j<=n;j++) {
2906: printf("After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2907: fprintf(ficlog,"After xit[%d]= %12.7f p[%d]= %12.7f",j,xit[j],j,p[j]);
2908: if(j % ncovmodel == 0){
2909: printf("\n");
2910: fprintf(ficlog,"\n");
2911: }
2912: }
1.224 brouard 2913: #endif
1.234 brouard 2914: for (j=1;j<=n;j++) {
2915: xi[j][ibig]=xi[j][n]; /* Replace direction with biggest decrease by last direction n */
2916: xi[j][n]=xit[j]; /* and this nth direction by the by the average p_0 p_n */
2917: }
1.224 brouard 2918: #ifdef LINMINORIGINAL
2919: #else
1.234 brouard 2920: for (j=1, flatd=0;j<=n;j++) {
2921: if(flatdir[j]>0)
2922: flatd++;
2923: }
2924: if(flatd >0){
1.255 brouard 2925: printf("%d flat directions: ",flatd);
2926: fprintf(ficlog,"%d flat directions :",flatd);
1.234 brouard 2927: for (j=1;j<=n;j++) {
2928: if(flatdir[j]>0){
2929: printf("%d ",j);
2930: fprintf(ficlog,"%d ",j);
2931: }
2932: }
2933: printf("\n");
2934: fprintf(ficlog,"\n");
1.319 brouard 2935: #ifdef FLATSUP
2936: free_vector(xit,1,n);
2937: free_vector(xits,1,n);
2938: free_vector(ptt,1,n);
2939: free_vector(pt,1,n);
2940: return;
2941: #endif
1.234 brouard 2942: }
1.191 brouard 2943: #endif
1.234 brouard 2944: printf("Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2945: fprintf(ficlog,"Gaining to use new average direction of P0 P%d instead of biggest increase direction %d :\n",n,ibig);
2946:
1.126 brouard 2947: #ifdef DEBUG
1.234 brouard 2948: printf("Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2949: fprintf(ficlog,"Direction changed last moved %d in place of ibig=%d, new last is the average:\n",n,ibig);
2950: for(j=1;j<=n;j++){
2951: printf(" %lf",xit[j]);
2952: fprintf(ficlog," %lf",xit[j]);
2953: }
2954: printf("\n");
2955: fprintf(ficlog,"\n");
1.126 brouard 2956: #endif
1.192 brouard 2957: } /* end of t or directest negative */
1.224 brouard 2958: #ifdef POWELLNOF3INFF1TEST
1.192 brouard 2959: #else
1.234 brouard 2960: } /* end if (fptt < fp) */
1.192 brouard 2961: #endif
1.225 brouard 2962: #ifdef NODIRECTIONCHANGEDUNTILNITER /* No change in drections until some iterations are done */
1.234 brouard 2963: } /*NODIRECTIONCHANGEDUNTILNITER No change in drections until some iterations are done */
1.225 brouard 2964: #else
1.224 brouard 2965: #endif
1.234 brouard 2966: } /* loop iteration */
1.126 brouard 2967: }
1.234 brouard 2968:
1.126 brouard 2969: /**** Prevalence limit (stable or period prevalence) ****************/
1.234 brouard 2970:
1.235 brouard 2971: double **prevalim(double **prlim, int nlstate, double x[], double age, double **oldm, double **savm, double ftolpl, int *ncvyear, int ij, int nres)
1.234 brouard 2972: {
1.338 brouard 2973: /**< Computes the prevalence limit in each live state at age x and for covariate combination ij . Nicely done
1.279 brouard 2974: * (and selected quantitative values in nres)
2975: * by left multiplying the unit
2976: * matrix by transitions matrix until convergence is reached with precision ftolpl
2977: * Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I
2978: * Wx is row vector: population in state 1, population in state 2, population dead
2979: * or prevalence in state 1, prevalence in state 2, 0
2980: * newm is the matrix after multiplications, its rows are identical at a factor.
2981: * Inputs are the parameter, age, a tolerance for the prevalence limit ftolpl.
2982: * Output is prlim.
2983: * Initial matrix pimij
2984: */
1.206 brouard 2985: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
2986: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
2987: /* 0, 0 , 1} */
2988: /*
2989: * and after some iteration: */
2990: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
2991: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
2992: /* 0, 0 , 1} */
2993: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
2994: /* {0.51571254859325999, 0.4842874514067399, */
2995: /* 0.51326036147820708, 0.48673963852179264} */
2996: /* If we start from prlim again, prlim tends to a constant matrix */
1.234 brouard 2997:
1.332 brouard 2998: int i, ii,j,k, k1;
1.209 brouard 2999: double *min, *max, *meandiff, maxmax,sumnew=0.;
1.145 brouard 3000: /* double **matprod2(); */ /* test */
1.218 brouard 3001: double **out, cov[NCOVMAX+1], **pmij(); /* **pmmij is a global variable feeded with oldms etc */
1.126 brouard 3002: double **newm;
1.209 brouard 3003: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
1.203 brouard 3004: int ncvloop=0;
1.288 brouard 3005: int first=0;
1.169 brouard 3006:
1.209 brouard 3007: min=vector(1,nlstate);
3008: max=vector(1,nlstate);
3009: meandiff=vector(1,nlstate);
3010:
1.218 brouard 3011: /* Starting with matrix unity */
1.126 brouard 3012: for (ii=1;ii<=nlstate+ndeath;ii++)
3013: for (j=1;j<=nlstate+ndeath;j++){
3014: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3015: }
1.169 brouard 3016:
3017: cov[1]=1.;
3018:
3019: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
1.202 brouard 3020: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.126 brouard 3021: for(agefin=age-stepm/YEARM; agefin>=age-delaymax; agefin=agefin-stepm/YEARM){
1.202 brouard 3022: ncvloop++;
1.126 brouard 3023: newm=savm;
3024: /* Covariates have to be included here again */
1.138 brouard 3025: cov[2]=agefin;
1.319 brouard 3026: if(nagesqr==1){
3027: cov[3]= agefin*agefin;
3028: }
1.332 brouard 3029: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3030: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3031: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3032: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3033: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3034: }else{
3035: cov[2+nagesqr+k1]=precov[nres][k1];
3036: }
3037: }/* End of loop on model equation */
3038:
3039: /* Start of old code (replaced by a loop on position in the model equation */
3040: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only of the model *\/ */
3041: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3042: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; *\/ */
3043: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])]; */
3044: /* /\* model = 1 +age + V1*V3 + age*V1 + V2 + V1 + age*V2 + V3 + V3*age + V1*V2 */
3045: /* * k 1 2 3 4 5 6 7 8 */
3046: /* *cov[] 1 2 3 4 5 6 7 8 9 10 */
3047: /* *TypeVar[k] 2 1 0 0 1 0 1 2 */
3048: /* *Dummy[k] 0 2 0 0 2 0 2 0 */
3049: /* *Tvar[k] 4 1 2 1 2 3 3 5 */
3050: /* *nsd=3 (1) (2) (3) */
3051: /* *TvarsD[nsd] [1]=2 1 3 */
3052: /* *TnsdVar [2]=2 [1]=1 [3]=3 */
3053: /* *TvarsDind[nsd](=k) [1]=3 [2]=4 [3]=6 */
3054: /* *Tage[] [1]=1 [2]=2 [3]=3 */
3055: /* *Tvard[] [1][1]=1 [2][1]=1 */
3056: /* * [1][2]=3 [2][2]=2 */
3057: /* *Tprod[](=k) [1]=1 [2]=8 */
3058: /* *TvarsDp(=Tvar) [1]=1 [2]=2 [3]=3 [4]=5 */
3059: /* *TvarD (=k) [1]=1 [2]=3 [3]=4 [3]=6 [4]=6 */
3060: /* *TvarsDpType */
3061: /* *si model= 1 + age + V3 + V2*age + V2 + V3*age */
3062: /* * nsd=1 (1) (2) */
3063: /* *TvarsD[nsd] 3 2 */
3064: /* *TnsdVar (3)=1 (2)=2 */
3065: /* *TvarsDind[nsd](=k) [1]=1 [2]=3 */
3066: /* *Tage[] [1]=2 [2]= 3 */
3067: /* *\/ */
3068: /* /\* cov[++k1]=nbcode[TvarsD[k]][codtabm(ij,k)]; *\/ */
3069: /* /\* printf("prevalim Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); *\/ */
3070: /* } */
3071: /* for (k=1; k<=nsq;k++) { /\* For single quantitative varying covariates only of the model *\/ */
3072: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3073: /* /\* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline *\/ */
3074: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3075: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][resultmodel[nres][k1]] */
3076: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3077: /* /\* printf("prevalim Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); *\/ */
3078: /* } */
3079: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3080: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
3081: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3082: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
3083: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
3084: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3085: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
3086: /* } */
3087: /* /\* printf("prevalim Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); *\/ */
3088: /* } */
3089: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3090: /* /\* printf("prevalim Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2]); *\/ */
3091: /* if(Dummy[Tvard[k][1]]==0){ */
3092: /* if(Dummy[Tvard[k][2]]==0){ */
3093: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3094: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3095: /* }else{ */
3096: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3097: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
3098: /* } */
3099: /* }else{ */
3100: /* if(Dummy[Tvard[k][2]]==0){ */
3101: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3102: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
3103: /* }else{ */
3104: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3105: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
3106: /* } */
3107: /* } */
3108: /* } /\* End product without age *\/ */
3109: /* ENd of old code */
1.138 brouard 3110: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3111: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3112: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
1.145 brouard 3113: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3114: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.319 brouard 3115: /* age and covariate values of ij are in 'cov' */
1.142 brouard 3116: out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /* Bug Valgrind */
1.138 brouard 3117:
1.126 brouard 3118: savm=oldm;
3119: oldm=newm;
1.209 brouard 3120:
3121: for(j=1; j<=nlstate; j++){
3122: max[j]=0.;
3123: min[j]=1.;
3124: }
3125: for(i=1;i<=nlstate;i++){
3126: sumnew=0;
3127: for(k=1; k<=ndeath; k++) sumnew+=newm[i][nlstate+k];
3128: for(j=1; j<=nlstate; j++){
3129: prlim[i][j]= newm[i][j]/(1-sumnew);
3130: max[j]=FMAX(max[j],prlim[i][j]);
3131: min[j]=FMIN(min[j],prlim[i][j]);
3132: }
3133: }
3134:
1.126 brouard 3135: maxmax=0.;
1.209 brouard 3136: for(j=1; j<=nlstate; j++){
3137: meandiff[j]=(max[j]-min[j])/(max[j]+min[j])*2.; /* mean difference for each column */
3138: maxmax=FMAX(maxmax,meandiff[j]);
3139: /* printf(" age= %d meandiff[%d]=%f, agefin=%d max[%d]=%f min[%d]=%f maxmax=%f\n", (int)age, j, meandiff[j],(int)agefin, j, max[j], j, min[j],maxmax); */
1.169 brouard 3140: } /* j loop */
1.203 brouard 3141: *ncvyear= (int)age- (int)agefin;
1.208 brouard 3142: /* printf("maxmax=%lf maxmin=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, maxmin, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.126 brouard 3143: if(maxmax < ftolpl){
1.209 brouard 3144: /* printf("maxmax=%lf ncvloop=%ld, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
3145: free_vector(min,1,nlstate);
3146: free_vector(max,1,nlstate);
3147: free_vector(meandiff,1,nlstate);
1.126 brouard 3148: return prlim;
3149: }
1.288 brouard 3150: } /* agefin loop */
1.208 brouard 3151: /* After some age loop it doesn't converge */
1.288 brouard 3152: if(!first){
3153: first=1;
3154: printf("Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d). Others in log file only...\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
1.317 brouard 3155: fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
3156: }else if (first >=1 && first <10){
3157: fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
3158: first++;
3159: }else if (first ==10){
3160: fprintf(ficlog, "Warning: the stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.d years and %d loops. Try to lower 'ftolpl'. Youngest age to start was %d=(%d-%d).\n", (int)age, maxmax, ftolpl, *ncvyear, ncvloop, (int)(agefin+stepm/YEARM), (int)(age-stepm/YEARM), (int)delaymax);
3161: printf("Warning: the stable prevalence dit not converge. This warning came too often, IMaCh will stop notifying, even in its log file. Look at the graphs to appreciate the non convergence.\n");
3162: fprintf(ficlog,"Warning: the stable prevalence no convergence; too many cases, giving up noticing, even in log file\n");
3163: first++;
1.288 brouard 3164: }
3165:
1.209 brouard 3166: /* Try to lower 'ftol', for example from 1.e-8 to 6.e-9.\n", ftolpl, (int)age, (int)delaymax, (int)agefin, ncvloop, (int)age-(int)agefin); */
3167: free_vector(min,1,nlstate);
3168: free_vector(max,1,nlstate);
3169: free_vector(meandiff,1,nlstate);
1.208 brouard 3170:
1.169 brouard 3171: return prlim; /* should not reach here */
1.126 brouard 3172: }
3173:
1.217 brouard 3174:
3175: /**** Back Prevalence limit (stable or period prevalence) ****************/
3176:
1.218 brouard 3177: /* double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ageminpar, double agemaxpar, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, double ftolpl, int *ncvyear, int ij) */
3178: /* double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, double ftolpl, int *ncvyear, int ij) */
1.242 brouard 3179: double **bprevalim(double **bprlim, double ***prevacurrent, int nlstate, double x[], double age, double ftolpl, int *ncvyear, int ij, int nres)
1.217 brouard 3180: {
1.264 brouard 3181: /* Computes the prevalence limit in each live state at age x and for covariate combination ij (<=2**cptcoveff) by left multiplying the unit
1.217 brouard 3182: matrix by transitions matrix until convergence is reached with precision ftolpl */
3183: /* Wx= Wx-1 Px-1= Wx-2 Px-2 Px-1 = Wx-n Px-n ... Px-2 Px-1 I */
3184: /* Wx is row vector: population in state 1, population in state 2, population dead */
3185: /* or prevalence in state 1, prevalence in state 2, 0 */
3186: /* newm is the matrix after multiplications, its rows are identical at a factor */
3187: /* Initial matrix pimij */
3188: /* {0.85204250825084937, 0.13044499163996345, 0.017512500109187184, */
3189: /* 0.090851990222114765, 0.88271245433047185, 0.026435555447413338, */
3190: /* 0, 0 , 1} */
3191: /*
3192: * and after some iteration: */
3193: /* {0.45504275246439968, 0.42731458730878791, 0.11764266022681241, */
3194: /* 0.45201005341706885, 0.42865420071559901, 0.11933574586733192, */
3195: /* 0, 0 , 1} */
3196: /* And prevalence by suppressing the deaths are close to identical rows in prlim: */
3197: /* {0.51571254859325999, 0.4842874514067399, */
3198: /* 0.51326036147820708, 0.48673963852179264} */
3199: /* If we start from prlim again, prlim tends to a constant matrix */
3200:
1.332 brouard 3201: int i, ii,j,k, k1;
1.247 brouard 3202: int first=0;
1.217 brouard 3203: double *min, *max, *meandiff, maxmax,sumnew=0.;
3204: /* double **matprod2(); */ /* test */
3205: double **out, cov[NCOVMAX+1], **bmij();
3206: double **newm;
1.218 brouard 3207: double **dnewm, **doldm, **dsavm; /* for use */
3208: double **oldm, **savm; /* for use */
3209:
1.217 brouard 3210: double agefin, delaymax=200. ; /* 100 Max number of years to converge */
3211: int ncvloop=0;
3212:
3213: min=vector(1,nlstate);
3214: max=vector(1,nlstate);
3215: meandiff=vector(1,nlstate);
3216:
1.266 brouard 3217: dnewm=ddnewms; doldm=ddoldms; dsavm=ddsavms;
3218: oldm=oldms; savm=savms;
3219:
3220: /* Starting with matrix unity */
3221: for (ii=1;ii<=nlstate+ndeath;ii++)
3222: for (j=1;j<=nlstate+ndeath;j++){
1.217 brouard 3223: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
3224: }
3225:
3226: cov[1]=1.;
3227:
3228: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3229: /* Start at agefin= age, computes the matrix of passage and loops decreasing agefin until convergence is reached */
1.218 brouard 3230: /* for(agefin=age+stepm/YEARM; agefin<=age+delaymax; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
1.288 brouard 3231: /* for(agefin=age; agefin<AGESUP; agefin=agefin+stepm/YEARM){ /\* A changer en age *\/ */
3232: for(agefin=age; agefin<FMIN(AGESUP,age+delaymax); agefin=agefin+stepm/YEARM){ /* A changer en age */
1.217 brouard 3233: ncvloop++;
1.218 brouard 3234: newm=savm; /* oldm should be kept from previous iteration or unity at start */
3235: /* newm points to the allocated table savm passed by the function it can be written, savm could be reallocated */
1.217 brouard 3236: /* Covariates have to be included here again */
3237: cov[2]=agefin;
1.319 brouard 3238: if(nagesqr==1){
1.217 brouard 3239: cov[3]= agefin*agefin;;
1.319 brouard 3240: }
1.332 brouard 3241: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3242: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3243: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.242 brouard 3244: }else{
1.332 brouard 3245: cov[2+nagesqr+k1]=precov[nres][k1];
1.242 brouard 3246: }
1.332 brouard 3247: }/* End of loop on model equation */
3248:
3249: /* Old code */
3250:
3251: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
3252: /* /\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\/ */
3253: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])]; */
3254: /* /\* printf("bprevalim Dummy agefin=%.0f combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov[%d]=%lf codtabm(%d,Tvar[%d])=%d \n",agefin,ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],2+nagesqr+TvarsDind[k],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); *\/ */
3255: /* } */
3256: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
3257: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3258: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3259: /* /\* /\\* printf("prevalim ij=%d k=%d Tvar[%d]=%d nbcode=%d cov=%lf codtabm(%d,Tvar[%d])=%d \n",ij,k, k, Tvar[k],nbcode[Tvar[k]][codtabm(ij,Tvar[k])],cov[2+k], ij, k, codtabm(ij,Tvar[k])]); *\\/ *\/ */
3260: /* /\* } *\/ */
3261: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3262: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3263: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3264: /* /\* printf("prevalim Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); *\/ */
3265: /* } */
3266: /* /\* for (k=1; k<=cptcovage;k++) cov[2+nagesqr+Tage[k]]=nbcode[Tvar[k]][codtabm(ij,k)]*cov[2]; *\/ */
3267: /* /\* for (k=1; k<=cptcovprod;k++) /\\* Useless *\\/ *\/ */
3268: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; *\\/ *\/ */
3269: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3270: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
3271: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age *\\/ ERROR ???*\/ */
3272: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3273: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3274: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3275: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3276: /* } */
3277: /* /\* printf("prevalim Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); *\/ */
3278: /* } */
3279: /* for (k=1; k<=cptcovprod;k++){ /\* For product without age *\/ */
3280: /* /\* printf("prevalim Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2]); *\/ */
3281: /* if(Dummy[Tvard[k][1]]==0){ */
3282: /* if(Dummy[Tvard[k][2]]==0){ */
3283: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3284: /* }else{ */
3285: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3286: /* } */
3287: /* }else{ */
3288: /* if(Dummy[Tvard[k][2]]==0){ */
3289: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3290: /* }else{ */
3291: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3292: /* } */
3293: /* } */
3294: /* } */
1.217 brouard 3295:
3296: /*printf("ij=%d cptcovprod=%d tvar=%d ", ij, cptcovprod, Tvar[1]);*/
3297: /*printf("ij=%d cov[3]=%lf cov[4]=%lf \n",ij, cov[3],cov[4]);*/
3298: /*printf("ij=%d cov[3]=%lf \n",ij, cov[3]);*/
3299: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
3300: /* out=matprod2(newm, pmij(pmmij,cov,ncovmodel,x,nlstate),1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); /\* Bug Valgrind *\/ */
1.218 brouard 3301: /* ij should be linked to the correct index of cov */
3302: /* age and covariate values ij are in 'cov', but we need to pass
3303: * ij for the observed prevalence at age and status and covariate
3304: * number: prevacurrent[(int)agefin][ii][ij]
3305: */
3306: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, ageminpar, agemaxpar, dnewm, doldm, dsavm,ij)); /\* Bug Valgrind *\/ */
3307: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij)); /\* Bug Valgrind *\/ */
3308: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij)); /* Bug Valgrind */
1.268 brouard 3309: /* if((int)age == 86 || (int)age == 87){ */
1.266 brouard 3310: /* printf(" Backward prevalim age=%d agefin=%d \n", (int) age, (int) agefin); */
3311: /* for(i=1; i<=nlstate+ndeath; i++) { */
3312: /* printf("%d newm= ",i); */
3313: /* for(j=1;j<=nlstate+ndeath;j++) { */
3314: /* printf("%f ",newm[i][j]); */
3315: /* } */
3316: /* printf("oldm * "); */
3317: /* for(j=1;j<=nlstate+ndeath;j++) { */
3318: /* printf("%f ",oldm[i][j]); */
3319: /* } */
1.268 brouard 3320: /* printf(" bmmij "); */
1.266 brouard 3321: /* for(j=1;j<=nlstate+ndeath;j++) { */
3322: /* printf("%f ",pmmij[i][j]); */
3323: /* } */
3324: /* printf("\n"); */
3325: /* } */
3326: /* } */
1.217 brouard 3327: savm=oldm;
3328: oldm=newm;
1.266 brouard 3329:
1.217 brouard 3330: for(j=1; j<=nlstate; j++){
3331: max[j]=0.;
3332: min[j]=1.;
3333: }
3334: for(j=1; j<=nlstate; j++){
3335: for(i=1;i<=nlstate;i++){
1.234 brouard 3336: /* bprlim[i][j]= newm[i][j]/(1-sumnew); */
3337: bprlim[i][j]= newm[i][j];
3338: max[i]=FMAX(max[i],bprlim[i][j]); /* Max in line */
3339: min[i]=FMIN(min[i],bprlim[i][j]);
1.217 brouard 3340: }
3341: }
1.218 brouard 3342:
1.217 brouard 3343: maxmax=0.;
3344: for(i=1; i<=nlstate; i++){
1.318 brouard 3345: meandiff[i]=(max[i]-min[i])/(max[i]+min[i])*2.; /* mean difference for each column, could be nan! */
1.217 brouard 3346: maxmax=FMAX(maxmax,meandiff[i]);
3347: /* printf("Back age= %d meandiff[%d]=%f, agefin=%d max[%d]=%f min[%d]=%f maxmax=%f\n", (int)age, i, meandiff[i],(int)agefin, i, max[i], i, min[i],maxmax); */
1.268 brouard 3348: } /* i loop */
1.217 brouard 3349: *ncvyear= -( (int)age- (int)agefin);
1.268 brouard 3350: /* printf("Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3351: if(maxmax < ftolpl){
1.220 brouard 3352: /* printf("OK Back maxmax=%lf ncvloop=%d, age=%d, agefin=%d ncvyear=%d \n", maxmax, ncvloop, (int)age, (int)agefin, *ncvyear); */
1.217 brouard 3353: free_vector(min,1,nlstate);
3354: free_vector(max,1,nlstate);
3355: free_vector(meandiff,1,nlstate);
3356: return bprlim;
3357: }
1.288 brouard 3358: } /* agefin loop */
1.217 brouard 3359: /* After some age loop it doesn't converge */
1.288 brouard 3360: if(!first){
1.247 brouard 3361: first=1;
3362: printf("Warning: the back stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.0f years. Try to lower 'ftolpl'. Others in log file only...\n\
3363: Oldest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear);
3364: }
3365: fprintf(ficlog,"Warning: the back stable prevalence at age %d did not converge with the required precision (%g > ftolpl=%g) within %.0f years. Try to lower 'ftolpl'. \n\
1.217 brouard 3366: Oldest age to start was %d-%d=%d, ncvloop=%d, ncvyear=%d\n", (int)age, maxmax, ftolpl, delaymax, (int)age, (int)delaymax, (int)agefin, ncvloop, *ncvyear);
3367: /* Try to lower 'ftol', for example from 1.e-8 to 6.e-9.\n", ftolpl, (int)age, (int)delaymax, (int)agefin, ncvloop, (int)age-(int)agefin); */
3368: free_vector(min,1,nlstate);
3369: free_vector(max,1,nlstate);
3370: free_vector(meandiff,1,nlstate);
3371:
3372: return bprlim; /* should not reach here */
3373: }
3374:
1.126 brouard 3375: /*************** transition probabilities ***************/
3376:
3377: double **pmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
3378: {
1.138 brouard 3379: /* According to parameters values stored in x and the covariate's values stored in cov,
1.266 brouard 3380: computes the probability to be observed in state j (after stepm years) being in state i by appying the
1.138 brouard 3381: model to the ncovmodel covariates (including constant and age).
3382: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3383: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3384: ncth covariate in the global vector x is given by the formula:
3385: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3386: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3387: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3388: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
1.266 brouard 3389: Outputs ps[i][j] or probability to be observed in j being in i according to
1.138 brouard 3390: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
1.266 brouard 3391: Sum on j ps[i][j] should equal to 1.
1.138 brouard 3392: */
3393: double s1, lnpijopii;
1.126 brouard 3394: /*double t34;*/
1.164 brouard 3395: int i,j, nc, ii, jj;
1.126 brouard 3396:
1.223 brouard 3397: for(i=1; i<= nlstate; i++){
3398: for(j=1; j<i;j++){
3399: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3400: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3401: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3402: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3403: }
3404: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3405: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3406: }
3407: for(j=i+1; j<=nlstate+ndeath;j++){
3408: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3409: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3410: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3411: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3412: }
3413: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
1.330 brouard 3414: /* printf("Debug pmij() i=%d j=%d nc=%d s1=%.17f, lnpijopii=%.17f\n",i,j,nc, s1,lnpijopii); */
1.223 brouard 3415: }
3416: }
1.218 brouard 3417:
1.223 brouard 3418: for(i=1; i<= nlstate; i++){
3419: s1=0;
3420: for(j=1; j<i; j++){
1.339 brouard 3421: /* printf("debug1 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3422: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3423: }
3424: for(j=i+1; j<=nlstate+ndeath; j++){
1.339 brouard 3425: /* printf("debug2 %d %d ps=%lf exp(ps)=%lf \n",i,j,ps[i][j],exp(ps[i][j])); */
1.223 brouard 3426: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3427: }
3428: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3429: ps[i][i]=1./(s1+1.);
3430: /* Computing other pijs */
3431: for(j=1; j<i; j++)
1.325 brouard 3432: ps[i][j]= exp(ps[i][j])*ps[i][i];/* Bug valgrind */
1.223 brouard 3433: for(j=i+1; j<=nlstate+ndeath; j++)
3434: ps[i][j]= exp(ps[i][j])*ps[i][i];
3435: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3436: } /* end i */
1.218 brouard 3437:
1.223 brouard 3438: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3439: for(jj=1; jj<= nlstate+ndeath; jj++){
3440: ps[ii][jj]=0;
3441: ps[ii][ii]=1;
3442: }
3443: }
1.294 brouard 3444:
3445:
1.223 brouard 3446: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3447: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3448: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3449: /* } */
3450: /* printf("\n "); */
3451: /* } */
3452: /* printf("\n ");printf("%lf ",cov[2]);*/
3453: /*
3454: for(i=1; i<= npar; i++) printf("%f ",x[i]);
1.218 brouard 3455: goto end;*/
1.266 brouard 3456: return ps; /* Pointer is unchanged since its call */
1.126 brouard 3457: }
3458:
1.218 brouard 3459: /*************** backward transition probabilities ***************/
3460:
3461: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ageminpar, double agemaxpar, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3462: /* double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, double ***dnewm, double **doldm, double **dsavm, int ij ) */
3463: double **bmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate, double ***prevacurrent, int ij )
3464: {
1.302 brouard 3465: /* Computes the backward probability at age agefin, cov[2], and covariate combination 'ij'. In fact cov is already filled and x too.
1.266 brouard 3466: * Call to pmij(cov and x), call to cross prevalence, sums and inverses, left multiply, and returns in **ps as well as **bmij.
1.222 brouard 3467: */
1.218 brouard 3468: int i, ii, j,k;
1.222 brouard 3469:
3470: double **out, **pmij();
3471: double sumnew=0.;
1.218 brouard 3472: double agefin;
1.292 brouard 3473: double k3=0.; /* constant of the w_x diagonal matrix (in order for B to sum to 1 even for death state) */
1.222 brouard 3474: double **dnewm, **dsavm, **doldm;
3475: double **bbmij;
3476:
1.218 brouard 3477: doldm=ddoldms; /* global pointers */
1.222 brouard 3478: dnewm=ddnewms;
3479: dsavm=ddsavms;
1.318 brouard 3480:
3481: /* Debug */
3482: /* printf("Bmij ij=%d, cov[2}=%f\n", ij, cov[2]); */
1.222 brouard 3483: agefin=cov[2];
1.268 brouard 3484: /* Bx = Diag(w_x) P_x Diag(Sum_i w^i_x p^ij_x */
1.222 brouard 3485: /* bmij *//* age is cov[2], ij is included in cov, but we need for
1.266 brouard 3486: the observed prevalence (with this covariate ij) at beginning of transition */
3487: /* dsavm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
1.268 brouard 3488:
3489: /* P_x */
1.325 brouard 3490: pmmij=pmij(pmmij,cov,ncovmodel,x,nlstate); /*This is forward probability from agefin to agefin + stepm *//* Bug valgrind */
1.268 brouard 3491: /* outputs pmmij which is a stochastic matrix in row */
3492:
3493: /* Diag(w_x) */
1.292 brouard 3494: /* Rescaling the cross-sectional prevalence: Problem with prevacurrent which can be zero */
1.268 brouard 3495: sumnew=0.;
1.269 brouard 3496: /*for (ii=1;ii<=nlstate+ndeath;ii++){*/
1.268 brouard 3497: for (ii=1;ii<=nlstate;ii++){ /* Only on live states */
1.297 brouard 3498: /* printf(" agefin=%d, ii=%d, ij=%d, prev=%f\n",(int)agefin,ii, ij, prevacurrent[(int)agefin][ii][ij]); */
1.268 brouard 3499: sumnew+=prevacurrent[(int)agefin][ii][ij];
3500: }
3501: if(sumnew >0.01){ /* At least some value in the prevalence */
3502: for (ii=1;ii<=nlstate+ndeath;ii++){
3503: for (j=1;j<=nlstate+ndeath;j++)
1.269 brouard 3504: doldm[ii][j]=(ii==j ? prevacurrent[(int)agefin][ii][ij]/sumnew : 0.0);
1.268 brouard 3505: }
3506: }else{
3507: for (ii=1;ii<=nlstate+ndeath;ii++){
3508: for (j=1;j<=nlstate+ndeath;j++)
3509: doldm[ii][j]=(ii==j ? 1./nlstate : 0.0);
3510: }
3511: /* if(sumnew <0.9){ */
3512: /* printf("Problem internal bmij B: sum on i wi <0.9: j=%d, sum_i wi=%lf,agefin=%d\n",j,sumnew, (int)agefin); */
3513: /* } */
3514: }
3515: k3=0.0; /* We put the last diagonal to 0 */
3516: for (ii=nlstate+1;ii<=nlstate+ndeath;ii++){
3517: doldm[ii][ii]= k3;
3518: }
3519: /* End doldm, At the end doldm is diag[(w_i)] */
3520:
1.292 brouard 3521: /* Left product of this diag matrix by pmmij=Px (dnewm=dsavm*doldm): diag[(w_i)*Px */
3522: bbmij=matprod2(dnewm, doldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, pmmij); /* was a Bug Valgrind */
1.268 brouard 3523:
1.292 brouard 3524: /* Diag(Sum_i w^i_x p^ij_x, should be the prevalence at age x+stepm */
1.268 brouard 3525: /* w1 p11 + w2 p21 only on live states N1./N..*N11/N1. + N2./N..*N21/N2.=(N11+N21)/N..=N.1/N.. */
1.222 brouard 3526: for (j=1;j<=nlstate+ndeath;j++){
1.268 brouard 3527: sumnew=0.;
1.222 brouard 3528: for (ii=1;ii<=nlstate;ii++){
1.266 brouard 3529: /* sumnew+=dsavm[ii][j]*prevacurrent[(int)agefin][ii][ij]; */
1.268 brouard 3530: sumnew+=pmmij[ii][j]*doldm[ii][ii]; /* Yes prevalence at beginning of transition */
1.222 brouard 3531: } /* sumnew is (N11+N21)/N..= N.1/N.. = sum on i of w_i pij */
1.268 brouard 3532: for (ii=1;ii<=nlstate+ndeath;ii++){
1.222 brouard 3533: /* if(agefin >= agemaxpar && agefin <= agemaxpar+stepm/YEARM){ */
1.268 brouard 3534: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3535: /* }else if(agefin >= agemaxpar+stepm/YEARM){ */
1.268 brouard 3536: /* dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0); */
1.222 brouard 3537: /* }else */
1.268 brouard 3538: dsavm[ii][j]=(ii==j ? 1./sumnew : 0.0);
3539: } /*End ii */
3540: } /* End j, At the end dsavm is diag[1/(w_1p1i+w_2 p2i)] for ALL states even if the sum is only for live states */
3541:
1.292 brouard 3542: ps=matprod2(ps, dnewm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, dsavm); /* was a Bug Valgrind */
1.268 brouard 3543: /* ps is now diag[w_i] * Px * diag [1/(w_1p1i+w_2 p2i)] */
1.222 brouard 3544: /* end bmij */
1.266 brouard 3545: return ps; /*pointer is unchanged */
1.218 brouard 3546: }
1.217 brouard 3547: /*************** transition probabilities ***************/
3548:
1.218 brouard 3549: double **bpmij(double **ps, double *cov, int ncovmodel, double *x, int nlstate )
1.217 brouard 3550: {
3551: /* According to parameters values stored in x and the covariate's values stored in cov,
3552: computes the probability to be observed in state j being in state i by appying the
3553: model to the ncovmodel covariates (including constant and age).
3554: lnpijopii=ln(pij/pii)= aij+bij*age+cij*v1+dij*v2+... = sum_nc=1^ncovmodel xij(nc)*cov[nc]
3555: and, according on how parameters are entered, the position of the coefficient xij(nc) of the
3556: ncth covariate in the global vector x is given by the formula:
3557: j<i nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel
3558: j>=i nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel
3559: Computes ln(pij/pii) (lnpijopii), deduces pij/pii by exponentiation,
3560: sums on j different of i to get 1-pii/pii, deduces pii, and then all pij.
3561: Outputs ps[i][j] the probability to be observed in j being in j according to
3562: the values of the covariates cov[nc] and corresponding parameter values x[nc+shiftij]
3563: */
3564: double s1, lnpijopii;
3565: /*double t34;*/
3566: int i,j, nc, ii, jj;
3567:
1.234 brouard 3568: for(i=1; i<= nlstate; i++){
3569: for(j=1; j<i;j++){
3570: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3571: /*lnpijopii += param[i][j][nc]*cov[nc];*/
3572: lnpijopii += x[nc+((i-1)*(nlstate+ndeath-1)+j-1)*ncovmodel]*cov[nc];
3573: /* printf("Int j<i s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3574: }
3575: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3576: /* printf("s1=%.17e, lnpijopii=%.17e\n",s1,lnpijopii); */
3577: }
3578: for(j=i+1; j<=nlstate+ndeath;j++){
3579: for (nc=1, lnpijopii=0.;nc <=ncovmodel; nc++){
3580: /*lnpijopii += x[(i-1)*nlstate*ncovmodel+(j-2)*ncovmodel+nc+(i-1)*(ndeath-1)*ncovmodel]*cov[nc];*/
3581: lnpijopii += x[nc + ((i-1)*(nlstate+ndeath-1)+(j-2))*ncovmodel]*cov[nc];
3582: /* printf("Int j>i s1=%.17e, lnpijopii=%.17e %lx %lx\n",s1,lnpijopii,s1,lnpijopii); */
3583: }
3584: ps[i][j]=lnpijopii; /* In fact ln(pij/pii) */
3585: }
3586: }
3587:
3588: for(i=1; i<= nlstate; i++){
3589: s1=0;
3590: for(j=1; j<i; j++){
3591: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3592: /*printf("debug1 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3593: }
3594: for(j=i+1; j<=nlstate+ndeath; j++){
3595: s1+=exp(ps[i][j]); /* In fact sums pij/pii */
3596: /*printf("debug2 %d %d ps=%lf exp(ps)=%lf s1+=%lf\n",i,j,ps[i][j],exp(ps[i][j]),s1); */
3597: }
3598: /* s1= sum_{j<>i} pij/pii=(1-pii)/pii and thus pii is known from s1 */
3599: ps[i][i]=1./(s1+1.);
3600: /* Computing other pijs */
3601: for(j=1; j<i; j++)
3602: ps[i][j]= exp(ps[i][j])*ps[i][i];
3603: for(j=i+1; j<=nlstate+ndeath; j++)
3604: ps[i][j]= exp(ps[i][j])*ps[i][i];
3605: /* ps[i][nlstate+1]=1.-s1- ps[i][i];*/ /* Sum should be 1 */
3606: } /* end i */
3607:
3608: for(ii=nlstate+1; ii<= nlstate+ndeath; ii++){
3609: for(jj=1; jj<= nlstate+ndeath; jj++){
3610: ps[ii][jj]=0;
3611: ps[ii][ii]=1;
3612: }
3613: }
1.296 brouard 3614: /* Added for prevbcast */ /* Transposed matrix too */
1.234 brouard 3615: for(jj=1; jj<= nlstate+ndeath; jj++){
3616: s1=0.;
3617: for(ii=1; ii<= nlstate+ndeath; ii++){
3618: s1+=ps[ii][jj];
3619: }
3620: for(ii=1; ii<= nlstate; ii++){
3621: ps[ii][jj]=ps[ii][jj]/s1;
3622: }
3623: }
3624: /* Transposition */
3625: for(jj=1; jj<= nlstate+ndeath; jj++){
3626: for(ii=jj; ii<= nlstate+ndeath; ii++){
3627: s1=ps[ii][jj];
3628: ps[ii][jj]=ps[jj][ii];
3629: ps[jj][ii]=s1;
3630: }
3631: }
3632: /* for(ii=1; ii<= nlstate+ndeath; ii++){ */
3633: /* for(jj=1; jj<= nlstate+ndeath; jj++){ */
3634: /* printf(" pmij ps[%d][%d]=%lf ",ii,jj,ps[ii][jj]); */
3635: /* } */
3636: /* printf("\n "); */
3637: /* } */
3638: /* printf("\n ");printf("%lf ",cov[2]);*/
3639: /*
3640: for(i=1; i<= npar; i++) printf("%f ",x[i]);
3641: goto end;*/
3642: return ps;
1.217 brouard 3643: }
3644:
3645:
1.126 brouard 3646: /**************** Product of 2 matrices ******************/
3647:
1.145 brouard 3648: double **matprod2(double **out, double **in,int nrl, int nrh, int ncl, int nch, int ncolol, int ncoloh, double **b)
1.126 brouard 3649: {
3650: /* Computes the matrix product of in(1,nrh-nrl+1)(1,nch-ncl+1) times
3651: b(1,nch-ncl+1)(1,ncoloh-ncolol+1) into out(...) */
3652: /* in, b, out are matrice of pointers which should have been initialized
3653: before: only the contents of out is modified. The function returns
3654: a pointer to pointers identical to out */
1.145 brouard 3655: int i, j, k;
1.126 brouard 3656: for(i=nrl; i<= nrh; i++)
1.145 brouard 3657: for(k=ncolol; k<=ncoloh; k++){
3658: out[i][k]=0.;
3659: for(j=ncl; j<=nch; j++)
3660: out[i][k] +=in[i][j]*b[j][k];
3661: }
1.126 brouard 3662: return out;
3663: }
3664:
3665:
3666: /************* Higher Matrix Product ***************/
3667:
1.235 brouard 3668: double ***hpxij(double ***po, int nhstepm, double age, int hstepm, double *x, int nlstate, int stepm, double **oldm, double **savm, int ij, int nres )
1.126 brouard 3669: {
1.336 brouard 3670: /* Already optimized with precov.
3671: Computes the transition matrix starting at age 'age' and dummies values in each resultline (loop on ij to find the corresponding combination) to over
1.126 brouard 3672: 'nhstepm*hstepm*stepm' months (i.e. until
3673: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3674: nhstepm*hstepm matrices.
3675: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3676: (typically every 2 years instead of every month which is too big
3677: for the memory).
3678: Model is determined by parameters x and covariates have to be
3679: included manually here.
3680:
3681: */
3682:
1.330 brouard 3683: int i, j, d, h, k, k1;
1.131 brouard 3684: double **out, cov[NCOVMAX+1];
1.126 brouard 3685: double **newm;
1.187 brouard 3686: double agexact;
1.214 brouard 3687: double agebegin, ageend;
1.126 brouard 3688:
3689: /* Hstepm could be zero and should return the unit matrix */
3690: for (i=1;i<=nlstate+ndeath;i++)
3691: for (j=1;j<=nlstate+ndeath;j++){
3692: oldm[i][j]=(i==j ? 1.0 : 0.0);
3693: po[i][j][0]=(i==j ? 1.0 : 0.0);
3694: }
3695: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3696: for(h=1; h <=nhstepm; h++){
3697: for(d=1; d <=hstepm; d++){
3698: newm=savm;
3699: /* Covariates have to be included here again */
3700: cov[1]=1.;
1.214 brouard 3701: agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /* age just before transition */
1.187 brouard 3702: cov[2]=agexact;
1.319 brouard 3703: if(nagesqr==1){
1.227 brouard 3704: cov[3]= agexact*agexact;
1.319 brouard 3705: }
1.330 brouard 3706: /* Model(2) V1 + V2 + V3 + V8 + V7*V8 + V5*V6 + V8*age + V3*age + age*age */
3707: /* total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age */
3708: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3709: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3710: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
3711: }else{
3712: cov[2+nagesqr+k1]=precov[nres][k1];
3713: }
3714: }/* End of loop on model equation */
3715: /* Old code */
3716: /* if( Dummy[k1]==0 && Typevar[k1]==0 ){ /\* Single dummy *\/ */
3717: /* /\* V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) *\/ */
3718: /* /\* for (k=1; k<=nsd;k++) { /\\* For single dummy covariates only *\\/ *\/ */
3719: /* /\* /\\* Here comes the value of the covariate 'ij' after renumbering k with single dummy covariates *\\/ *\/ */
3720: /* /\* codtabm(ij,k) (1 & (ij-1) >> (k-1))+1 *\/ */
3721: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3722: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3723: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
3724: /* /\* nsd 1 2 3 *\/ /\* Counting single dummies covar fixed or tv *\/ */
3725: /* /\*TvarsD[nsd] 4 3 1 *\/ /\* ID of single dummy cova fixed or timevary*\/ */
3726: /* /\*TvarsDind[k] 2 3 9 *\/ /\* position K of single dummy cova *\/ */
3727: /* /\* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,k)];or [codtabm(ij,TnsdVar[TvarsD[k]] *\/ */
3728: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3729: /* /\* printf("hpxij Dummy combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov=%lf codtabm(%d,TnsdVar[TvarsD[%d])=%d \n",ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,TnsdVar[TvarsD[k]])],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,TnsdVar[TvarsD[k]])); *\/ */
3730: /* printf("hpxij Dummy combi=%d k1=%d Tvar[%d]=V%d cov[2+%d+%d]=%lf resultmodel[nres][%d]=%d nres/nresult=%d/%d \n",ij,k1,k1, Tvar[k1],nagesqr,k1,cov[2+nagesqr+k1],k1,resultmodel[nres][k1],nres,nresult); */
3731: /* printf("hpxij new Dummy precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3732: /* }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /\* Single quantitative variables *\/ */
3733: /* /\* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline *\/ */
3734: /* cov[2+nagesqr+k1]=Tqresult[nres][resultmodel[nres][k1]]; */
3735: /* /\* for (k=1; k<=nsq;k++) { /\\* For single varying covariates only *\\/ *\/ */
3736: /* /\* /\\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\\/ *\/ */
3737: /* /\* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; *\/ */
3738: /* printf("hPxij Quantitative k1=%d resultmodel[nres][%d]=%d,Tqresult[%d][%d]=%f\n",k1,k1,resultmodel[nres][k1],nres,resultmodel[nres][k1],Tqresult[nres][resultmodel[nres][k1]]); */
3739: /* printf("hpxij new Quanti precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3740: /* }else if( Dummy[k1]==2 ){ /\* For dummy with age product *\/ */
3741: /* /\* Tvar[k1] Variable in the age product age*V1 is 1 *\/ */
3742: /* /\* [Tinvresult[nres][V1] is its value in the resultline nres *\/ */
3743: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvar[k1]]*cov[2]; */
3744: /* printf("DhPxij Dummy with age k1=%d Tvar[%d]=%d TinvDoQresult[nres=%d][%d]=%.f age=%.2f,cov[2+%d+%d]=%.3f\n",k1,k1,Tvar[k1],nres,TinvDoQresult[nres][Tvar[k1]],cov[2],nagesqr,k1,cov[2+nagesqr+k1]); */
3745: /* printf("hpxij new Dummy with age product precov[nres=%d][k1=%d]=%.4f * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3746:
3747: /* /\* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; *\/ */
3748: /* /\* for (k=1; k<=cptcovage;k++){ /\\* For product with age V1+V1*age +V4 +age*V3 *\\/ *\/ */
3749: /* /\* 1+2 Tage[1]=2 TVar[2]=1 Dummy[2]=2, Tage[2]=4 TVar[4]=3 Dummy[4]=3 quant*\/ */
3750: /* /\* *\/ */
1.330 brouard 3751: /* /\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\/ */
3752: /* /\* k 1 2 3 4 5 6 7 8 9 *\/ */
3753: /* /\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\/ */
1.332 brouard 3754: /* /\*cptcovage=2 1 2 *\/ */
3755: /* /\*Tage[k]= 5 8 *\/ */
3756: /* }else if( Dummy[k1]==3 ){ /\* For quant with age product *\/ */
3757: /* cov[2+nagesqr+k1]=Tresult[nres][resultmodel[nres][k1]]; */
3758: /* printf("QhPxij Quant with age k1=%d resultmodel[nres][%d]=%d,Tqresult[%d][%d]=%f\n",k1,k1,resultmodel[nres][k1],nres,resultmodel[nres][k1],Tqresult[nres][resultmodel[nres][k1]]); */
3759: /* printf("hpxij new Quanti with age product precov[nres=%d][k1=%d] * age=%.2f\n", nres, k1, precov[nres][k1], cov[2]); */
3760: /* /\* if(Dummy[Tage[k]]== 2){ /\\* dummy with age *\\/ *\/ */
3761: /* /\* /\\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\\* dummy with age *\\\/ *\\/ *\/ */
3762: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\\/ *\/ */
3763: /* /\* /\\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\\/ *\/ */
3764: /* /\* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[TvarsD[Tvar[Tage[k]]]])]*cov[2]; *\/ */
3765: /* /\* printf("hPxij Age combi=%d k=%d cptcovage=%d Tage[%d]=%d Tvar[Tage[%d]]=V%d nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[Tvar[Tage[k]]]])]=%d nres=%d\n",ij,k,cptcovage,k,Tage[k],k,Tvar[Tage[k]], nbcode[Tvar[Tage[k]]][codtabm(ij,TnsdVar[Tvar[Tage[k]]])],nres); *\/ */
3766: /* /\* } else if(Dummy[Tage[k]]== 3){ /\\* quantitative with age *\\/ *\/ */
3767: /* /\* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; *\/ */
3768: /* /\* } *\/ */
3769: /* /\* printf("hPxij Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); *\/ */
3770: /* }else if(Typevar[k1]==2 ){ /\* For product (not with age) *\/ */
3771: /* /\* for (k=1; k<=cptcovprod;k++){ /\\* For product without age *\\/ *\/ */
3772: /* /\* /\\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 *\\/ *\/ */
3773: /* /\* /\\* k 1 2 3 4 5 6 7 8 9 *\\/ *\/ */
3774: /* /\* /\\*Tvar[k]= 5 4 3 6 5 2 7 1 1 *\\/ *\/ */
3775: /* /\* /\\*cptcovprod=1 1 2 *\\/ *\/ */
3776: /* /\* /\\*Tprod[]= 4 7 *\\/ *\/ */
3777: /* /\* /\\*Tvard[][1] 4 1 *\\/ *\/ */
3778: /* /\* /\\*Tvard[][2] 3 2 *\\/ *\/ */
1.330 brouard 3779:
1.332 brouard 3780: /* /\* printf("hPxij Prod ij=%d k=%d Tprod[%d]=%d Tvard[%d][1]=V%d, Tvard[%d][2]=V%d nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]=%d nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]=%d\n",ij,k,k,Tprod[k], k,Tvard[k][1], k,Tvard[k][2],nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])],nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]); *\/ */
3781: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3782: /* cov[2+nagesqr+k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]]; */
3783: /* printf("hPxij Prod ij=%d k1=%d cov[2+%d+%d]=%.5f Tvard[%d][1]=V%d * Tvard[%d][2]=V%d ; TinvDoQresult[nres][Tvardk[k1][1]]=%.4f * TinvDoQresult[nres][Tvardk[k1][1]]=%.4f\n",ij,k1,nagesqr,k1,cov[2+nagesqr+k1],k1,Tvardk[k1][1], k1,Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][1]], TinvDoQresult[nres][Tvardk[k1][2]]); */
3784: /* printf("hpxij new Product no age product precov[nres=%d][k1=%d]=%.4f\n", nres, k1, precov[nres][k1]); */
3785:
3786: /* /\* if(Dummy[Tvardk[k1][1]]==0){ *\/ */
3787: /* /\* if(Dummy[Tvardk[k1][2]]==0){ /\\* Product of dummies *\\/ *\/ */
3788: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
3789: /* /\* cov[2+nagesqr+k1]=Tinvresult[nres][Tvardk[k1][1]] * Tinvresult[nres][Tvardk[k1][2]]; *\/ */
3790: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])]; *\/ */
3791: /* /\* }else{ /\\* Product of dummy by quantitative *\\/ *\/ */
3792: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,TnsdVar[Tvard[k][1]])] * Tqresult[nres][k]; *\/ */
3793: /* /\* cov[2+nagesqr+k1]=Tresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]]; *\/ */
3794: /* /\* } *\/ */
3795: /* /\* }else{ /\\* Product of quantitative by...*\\/ *\/ */
3796: /* /\* if(Dummy[Tvard[k][2]]==0){ /\\* quant by dummy *\\/ *\/ */
3797: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][Tvard[k][1]]; *\\/ *\/ */
3798: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3799: /* /\* }else{ /\\* Product of two quant *\\/ *\/ */
3800: /* /\* /\\* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\\/ *\/ */
3801: /* /\* cov[2+nagesqr+k1]=Tqresult[nres][Tinvresult[nres][Tvardk[k1][1]]] * Tqresult[nres][Tinvresult[nres][Tvardk[k1][2]]] ; *\/ */
3802: /* /\* } *\/ */
3803: /* /\* }/\\*end of products quantitative *\\/ *\/ */
3804: /* }/\*end of products *\/ */
3805: /* } /\* End of loop on model equation *\/ */
1.235 brouard 3806: /* for (k=1; k<=cptcovn;k++) */
3807: /* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; */
3808: /* for (k=1; k<=cptcovage;k++) /\* Should start at cptcovn+1 *\/ */
3809: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; */
3810: /* for (k=1; k<=cptcovprod;k++) /\* Useless because included in cptcovn *\/ */
3811: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; */
1.227 brouard 3812:
3813:
1.126 brouard 3814: /*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*/
3815: /*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*/
1.319 brouard 3816: /* right multiplication of oldm by the current matrix */
1.126 brouard 3817: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath,
3818: pmij(pmmij,cov,ncovmodel,x,nlstate));
1.217 brouard 3819: /* if((int)age == 70){ */
3820: /* printf(" Forward hpxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3821: /* for(i=1; i<=nlstate+ndeath; i++) { */
3822: /* printf("%d pmmij ",i); */
3823: /* for(j=1;j<=nlstate+ndeath;j++) { */
3824: /* printf("%f ",pmmij[i][j]); */
3825: /* } */
3826: /* printf(" oldm "); */
3827: /* for(j=1;j<=nlstate+ndeath;j++) { */
3828: /* printf("%f ",oldm[i][j]); */
3829: /* } */
3830: /* printf("\n"); */
3831: /* } */
3832: /* } */
1.126 brouard 3833: savm=oldm;
3834: oldm=newm;
3835: }
3836: for(i=1; i<=nlstate+ndeath; i++)
3837: for(j=1;j<=nlstate+ndeath;j++) {
1.267 brouard 3838: po[i][j][h]=newm[i][j];
3839: /*if(h==nhstepm) printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]);*/
1.126 brouard 3840: }
1.128 brouard 3841: /*printf("h=%d ",h);*/
1.126 brouard 3842: } /* end h */
1.267 brouard 3843: /* printf("\n H=%d \n",h); */
1.126 brouard 3844: return po;
3845: }
3846:
1.217 brouard 3847: /************* Higher Back Matrix Product ***************/
1.218 brouard 3848: /* double ***hbxij(double ***po, int nhstepm, double age, int hstepm, double *x, double ***prevacurrent, int nlstate, int stepm, double **oldm, double **savm, double **dnewm, double **doldm, double **dsavm, int ij ) */
1.267 brouard 3849: double ***hbxij(double ***po, int nhstepm, double age, int hstepm, double *x, double ***prevacurrent, int nlstate, int stepm, int ij, int nres )
1.217 brouard 3850: {
1.332 brouard 3851: /* For dummy covariates given in each resultline (for historical, computes the corresponding combination ij),
3852: computes the transition matrix starting at age 'age' over
1.217 brouard 3853: 'nhstepm*hstepm*stepm' months (i.e. until
1.218 brouard 3854: age (in years) age+nhstepm*hstepm*stepm/12) by multiplying
3855: nhstepm*hstepm matrices.
3856: Output is stored in matrix po[i][j][h] for h every 'hstepm' step
3857: (typically every 2 years instead of every month which is too big
1.217 brouard 3858: for the memory).
1.218 brouard 3859: Model is determined by parameters x and covariates have to be
1.266 brouard 3860: included manually here. Then we use a call to bmij(x and cov)
3861: The addresss of po (p3mat allocated to the dimension of nhstepm) should be stored for output
1.222 brouard 3862: */
1.217 brouard 3863:
1.332 brouard 3864: int i, j, d, h, k, k1;
1.266 brouard 3865: double **out, cov[NCOVMAX+1], **bmij();
3866: double **newm, ***newmm;
1.217 brouard 3867: double agexact;
3868: double agebegin, ageend;
1.222 brouard 3869: double **oldm, **savm;
1.217 brouard 3870:
1.266 brouard 3871: newmm=po; /* To be saved */
3872: oldm=oldms;savm=savms; /* Global pointers */
1.217 brouard 3873: /* Hstepm could be zero and should return the unit matrix */
3874: for (i=1;i<=nlstate+ndeath;i++)
3875: for (j=1;j<=nlstate+ndeath;j++){
3876: oldm[i][j]=(i==j ? 1.0 : 0.0);
3877: po[i][j][0]=(i==j ? 1.0 : 0.0);
3878: }
3879: /* Even if hstepm = 1, at least one multiplication by the unit matrix */
3880: for(h=1; h <=nhstepm; h++){
3881: for(d=1; d <=hstepm; d++){
3882: newm=savm;
3883: /* Covariates have to be included here again */
3884: cov[1]=1.;
1.271 brouard 3885: agexact=age-( (h-1)*hstepm + (d) )*stepm/YEARM; /* age just before transition, d or d-1? */
1.217 brouard 3886: /* agexact=age+((h-1)*hstepm + (d-1))*stepm/YEARM; /\* age just before transition *\/ */
1.318 brouard 3887: /* Debug */
3888: /* printf("hBxij age=%lf, agexact=%lf\n", age, agexact); */
1.217 brouard 3889: cov[2]=agexact;
1.332 brouard 3890: if(nagesqr==1){
1.222 brouard 3891: cov[3]= agexact*agexact;
1.332 brouard 3892: }
3893: /** New code */
3894: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 3895: if(Typevar[k1]==1 || Typevar[k1]==3){ /* A product with age */
1.332 brouard 3896: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.325 brouard 3897: }else{
1.332 brouard 3898: cov[2+nagesqr+k1]=precov[nres][k1];
1.325 brouard 3899: }
1.332 brouard 3900: }/* End of loop on model equation */
3901: /** End of new code */
3902: /** This was old code */
3903: /* for (k=1; k<=nsd;k++){ /\* For single dummy covariates only *\//\* cptcovn error *\/ */
3904: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,k)]; *\/ */
3905: /* /\* /\\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; *\\/ *\/ */
3906: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(ij,TvarsD[k])];/\* Bug valgrind *\/ */
3907: /* /\* printf("hbxij Dummy agexact=%.0f combi=%d k=%d TvarsD[%d]=V%d TvarsDind[%d]=%d nbcode=%d cov[%d]=%lf codtabm(%d,Tvar[%d])=%d \n",agexact,ij,k, k, TvarsD[k],k,TvarsDind[k],nbcode[TvarsD[k]][codtabm(ij,k)],2+nagesqr+TvarsDind[k],cov[2+nagesqr+TvarsDind[k]], ij, k, codtabm(ij,k)); *\/ */
3908: /* } */
3909: /* for (k=1; k<=nsq;k++) { /\* For single varying covariates only *\/ */
3910: /* /\* Here comes the value of quantitative after renumbering k with single quantitative covariates *\/ */
3911: /* cov[2+nagesqr+TvarsQind[k]]=Tqresult[nres][k]; */
3912: /* /\* printf("hPxij Quantitative k=%d TvarsQind[%d]=%d, TvarsQ[%d]=V%d,Tqresult[%d][%d]=%f\n",k,k,TvarsQind[k],k,TvarsQ[k],nres,k,Tqresult[nres][k]); *\/ */
3913: /* } */
3914: /* for (k=1; k<=cptcovage;k++){ /\* Should start at cptcovn+1 *\//\* For product with age *\/ */
3915: /* /\* if(Dummy[Tvar[Tage[k]]]== 2){ /\\* dummy with age error!!!*\\/ *\/ */
3916: /* if(Dummy[Tage[k]]== 2){ /\* dummy with age *\/ */
3917: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k]])]*cov[2]; */
3918: /* } else if(Dummy[Tage[k]]== 3){ /\* quantitative with age *\/ */
3919: /* cov[2+nagesqr+Tage[k]]=Tqresult[nres][k]; */
3920: /* } */
3921: /* /\* printf("hBxij Age combi=%d k=%d Tage[%d]=V%d Tqresult[%d][%d]=%f\n",ij,k,k,Tage[k],nres,k,Tqresult[nres][k]); *\/ */
3922: /* } */
3923: /* for (k=1; k<=cptcovprod;k++){ /\* Useless because included in cptcovn *\/ */
3924: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])]*nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])]; */
3925: /* if(Dummy[Tvard[k][1]]==0){ */
3926: /* if(Dummy[Tvard[k][2]]==0){ */
3927: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][1])]; */
3928: /* }else{ */
3929: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,Tvard[k][1])] * Tqresult[nres][k]; */
3930: /* } */
3931: /* }else{ */
3932: /* if(Dummy[Tvard[k][2]]==0){ */
3933: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(ij,Tvard[k][2])] * Tqinvresult[nres][Tvard[k][1]]; */
3934: /* }else{ */
3935: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; */
3936: /* } */
3937: /* } */
3938: /* } */
3939: /* /\*printf("hxi cptcov=%d cptcode=%d\n",cptcov,cptcode);*\/ */
3940: /* /\*printf("h=%d d=%d age=%f cov=%f\n",h,d,age,cov[2]);*\/ */
3941: /** End of old code */
3942:
1.218 brouard 3943: /* Careful transposed matrix */
1.266 brouard 3944: /* age is in cov[2], prevacurrent at beginning of transition. */
1.218 brouard 3945: /* out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent, dnewm, doldm, dsavm,ij),\ */
1.222 brouard 3946: /* 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm); */
1.218 brouard 3947: out=matprod2(newm, bmij(pmmij,cov,ncovmodel,x,nlstate,prevacurrent,ij),\
1.325 brouard 3948: 1,nlstate+ndeath,1,nlstate+ndeath,1,nlstate+ndeath, oldm);/* Bug valgrind */
1.217 brouard 3949: /* if((int)age == 70){ */
3950: /* printf(" Backward hbxij age=%d agexact=%f d=%d nhstepm=%d hstepm=%d\n", (int) age, agexact, d, nhstepm, hstepm); */
3951: /* for(i=1; i<=nlstate+ndeath; i++) { */
3952: /* printf("%d pmmij ",i); */
3953: /* for(j=1;j<=nlstate+ndeath;j++) { */
3954: /* printf("%f ",pmmij[i][j]); */
3955: /* } */
3956: /* printf(" oldm "); */
3957: /* for(j=1;j<=nlstate+ndeath;j++) { */
3958: /* printf("%f ",oldm[i][j]); */
3959: /* } */
3960: /* printf("\n"); */
3961: /* } */
3962: /* } */
3963: savm=oldm;
3964: oldm=newm;
3965: }
3966: for(i=1; i<=nlstate+ndeath; i++)
3967: for(j=1;j<=nlstate+ndeath;j++) {
1.222 brouard 3968: po[i][j][h]=newm[i][j];
1.268 brouard 3969: /* if(h==nhstepm) */
3970: /* printf("po[%d][%d][%d]=%f ",i,j,h,po[i][j][h]); */
1.217 brouard 3971: }
1.268 brouard 3972: /* printf("h=%d %.1f ",h, agexact); */
1.217 brouard 3973: } /* end h */
1.268 brouard 3974: /* printf("\n H=%d nhs=%d \n",h, nhstepm); */
1.217 brouard 3975: return po;
3976: }
3977:
3978:
1.162 brouard 3979: #ifdef NLOPT
3980: double myfunc(unsigned n, const double *p1, double *grad, void *pd){
3981: double fret;
3982: double *xt;
3983: int j;
3984: myfunc_data *d2 = (myfunc_data *) pd;
3985: /* xt = (p1-1); */
3986: xt=vector(1,n);
3987: for (j=1;j<=n;j++) xt[j]=p1[j-1]; /* xt[1]=p1[0] */
3988:
3989: fret=(d2->function)(xt); /* p xt[1]@8 is fine */
3990: /* fret=(*func)(xt); /\* p xt[1]@8 is fine *\/ */
3991: printf("Function = %.12lf ",fret);
3992: for (j=1;j<=n;j++) printf(" %d %.8lf", j, xt[j]);
3993: printf("\n");
3994: free_vector(xt,1,n);
3995: return fret;
3996: }
3997: #endif
1.126 brouard 3998:
3999: /*************** log-likelihood *************/
4000: double func( double *x)
4001: {
1.336 brouard 4002: int i, ii, j, k, mi, d, kk, kf=0;
1.226 brouard 4003: int ioffset=0;
1.339 brouard 4004: int ipos=0,iposold=0,ncovv=0;
4005:
1.340 brouard 4006: double cotvarv, cotvarvold;
1.226 brouard 4007: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
4008: double **out;
4009: double lli; /* Individual log likelihood */
4010: int s1, s2;
1.228 brouard 4011: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
1.336 brouard 4012:
1.226 brouard 4013: double bbh, survp;
4014: double agexact;
1.336 brouard 4015: double agebegin, ageend;
1.226 brouard 4016: /*extern weight */
4017: /* We are differentiating ll according to initial status */
4018: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4019: /*for(i=1;i<imx;i++)
4020: printf(" %d\n",s[4][i]);
4021: */
1.162 brouard 4022:
1.226 brouard 4023: ++countcallfunc;
1.162 brouard 4024:
1.226 brouard 4025: cov[1]=1.;
1.126 brouard 4026:
1.226 brouard 4027: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4028: ioffset=0;
1.226 brouard 4029: if(mle==1){
4030: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4031: /* Computes the values of the ncovmodel covariates of the model
4032: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4033: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4034: to be observed in j being in i according to the model.
4035: */
1.243 brouard 4036: ioffset=2+nagesqr ;
1.233 brouard 4037: /* Fixed */
1.345 brouard 4038: for (kf=1; kf<=ncovf;kf++){ /* For each fixed covariate dummy or quant or prod */
1.319 brouard 4039: /* # V1=sex, V2=raedyrs Quant Fixed, State=livarnb4..livarnb11, V3=iadl4..iald11, V4=adlw4..adlw11, V5=r4bmi..r11bmi */
4040: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
4041: /* TvarF[1]=Tvar[6]=2, TvarF[2]=Tvar[7]=7, TvarF[3]=Tvar[9]=1 ID of fixed covariates or product V2, V1*V2, V1 */
1.320 brouard 4042: /* TvarFind; TvarFind[1]=6, TvarFind[2]=7, TvarFind[3]=9 *//* Inverse V2(6) is first fixed (single or prod) */
1.336 brouard 4043: cov[ioffset+TvarFind[kf]]=covar[Tvar[TvarFind[kf]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (TvarFind[1]=6)*/
1.319 brouard 4044: /* V1*V2 (7) TvarFind[2]=7, TvarFind[3]=9 */
1.234 brouard 4045: }
1.226 brouard 4046: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
1.319 brouard 4047: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
1.226 brouard 4048: has been calculated etc */
4049: /* For an individual i, wav[i] gives the number of effective waves */
4050: /* We compute the contribution to Likelihood of each effective transition
4051: mw[mi][i] is real wave of the mi th effectve wave */
4052: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4053: s2=s[mw[mi+1][i]][i];
1.341 brouard 4054: And the iv th varying covariate is the cotvar[mw[mi+1][i]][iv][i] because now is moved after nvocol+nqv
1.226 brouard 4055: But if the variable is not in the model TTvar[iv] is the real variable effective in the model:
4056: meaning that decodemodel should be used cotvar[mw[mi+1][i]][TTvar[iv]][i]
4057: */
1.336 brouard 4058: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
4059: /* Wave varying (but not age varying) */
1.339 brouard 4060: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates in the model (single and product but no age )"V5+V4+V3+V4*V3+V5*age+V1*age+V1" +TvarVind 1,2,3,4(V4*V3) Tvar[1]@7{5, 4, 3, 6, 5, 1, 1 ; 6 because the created covar is after V5 and is 6, minus 1+1, 3,2,1,4 positions in cotvar*\/ */
4061: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; but where is the crossproduct? *\/ */
4062: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4063: /* } */
1.340 brouard 4064: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age )*/
4065: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4066: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4067: if(FixedV[itv]!=0){ /* Not a fixed covariate */
1.341 brouard 4068: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* cotvar[wav][ncovcol+nqv+iv][i] */
1.340 brouard 4069: }else{ /* fixed covariate */
1.345 brouard 4070: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
1.340 brouard 4071: }
1.339 brouard 4072: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4073: cotvarvold=cotvarv;
4074: }else{ /* A second product */
4075: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4076: }
4077: iposold=ipos;
1.340 brouard 4078: cov[ioffset+ipos]=cotvarv;
1.234 brouard 4079: }
1.339 brouard 4080: /* for products of time varying to be done */
1.234 brouard 4081: for (ii=1;ii<=nlstate+ndeath;ii++)
4082: for (j=1;j<=nlstate+ndeath;j++){
4083: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4084: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4085: }
1.336 brouard 4086:
4087: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4088: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
1.234 brouard 4089: for(d=0; d<dh[mi][i]; d++){
4090: newm=savm;
4091: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4092: cov[2]=agexact;
4093: if(nagesqr==1)
4094: cov[3]= agexact*agexact; /* Should be changed here */
1.349 brouard 4095: /* for (kk=1; kk<=cptcovage;kk++) { */
4096: /* if(!FixedV[Tvar[Tage[kk]]]) */
4097: /* cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /\* Tage[kk] gives the data-covariate associated with age *\/ */
4098: /* else */
4099: /* cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4100: /* } */
4101: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4102: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4103: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4104: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4105: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4106: }else{ /* fixed covariate */
4107: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4108: }
4109: if(ipos!=iposold){ /* Not a product or first of a product */
4110: cotvarvold=cotvarv;
4111: }else{ /* A second product */
4112: cotvarv=cotvarv*cotvarvold;
4113: }
4114: iposold=ipos;
4115: cov[ioffset+ipos]=cotvarv*agexact;
4116: /* For products */
1.234 brouard 4117: }
1.349 brouard 4118:
1.234 brouard 4119: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4120: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4121: savm=oldm;
4122: oldm=newm;
4123: } /* end mult */
4124:
4125: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4126: /* But now since version 0.9 we anticipate for bias at large stepm.
4127: * If stepm is larger than one month (smallest stepm) and if the exact delay
4128: * (in months) between two waves is not a multiple of stepm, we rounded to
4129: * the nearest (and in case of equal distance, to the lowest) interval but now
4130: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4131: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4132: * probability in order to take into account the bias as a fraction of the way
1.231 brouard 4133: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4134: * -stepm/2 to stepm/2 .
4135: * For stepm=1 the results are the same as for previous versions of Imach.
4136: * For stepm > 1 the results are less biased than in previous versions.
4137: */
1.234 brouard 4138: s1=s[mw[mi][i]][i];
4139: s2=s[mw[mi+1][i]][i];
4140: bbh=(double)bh[mi][i]/(double)stepm;
4141: /* bias bh is positive if real duration
4142: * is higher than the multiple of stepm and negative otherwise.
4143: */
4144: /* lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2]));*/
4145: if( s2 > nlstate){
4146: /* i.e. if s2 is a death state and if the date of death is known
4147: then the contribution to the likelihood is the probability to
4148: die between last step unit time and current step unit time,
4149: which is also equal to probability to die before dh
4150: minus probability to die before dh-stepm .
4151: In version up to 0.92 likelihood was computed
4152: as if date of death was unknown. Death was treated as any other
4153: health state: the date of the interview describes the actual state
4154: and not the date of a change in health state. The former idea was
4155: to consider that at each interview the state was recorded
4156: (healthy, disable or death) and IMaCh was corrected; but when we
4157: introduced the exact date of death then we should have modified
4158: the contribution of an exact death to the likelihood. This new
4159: contribution is smaller and very dependent of the step unit
4160: stepm. It is no more the probability to die between last interview
4161: and month of death but the probability to survive from last
4162: interview up to one month before death multiplied by the
4163: probability to die within a month. Thanks to Chris
4164: Jackson for correcting this bug. Former versions increased
4165: mortality artificially. The bad side is that we add another loop
4166: which slows down the processing. The difference can be up to 10%
4167: lower mortality.
4168: */
4169: /* If, at the beginning of the maximization mostly, the
4170: cumulative probability or probability to be dead is
4171: constant (ie = 1) over time d, the difference is equal to
4172: 0. out[s1][3] = savm[s1][3]: probability, being at state
4173: s1 at precedent wave, to be dead a month before current
4174: wave is equal to probability, being at state s1 at
4175: precedent wave, to be dead at mont of the current
4176: wave. Then the observed probability (that this person died)
4177: is null according to current estimated parameter. In fact,
4178: it should be very low but not zero otherwise the log go to
4179: infinity.
4180: */
1.183 brouard 4181: /* #ifdef INFINITYORIGINAL */
4182: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4183: /* #else */
4184: /* if ((out[s1][s2] - savm[s1][s2]) < mytinydouble) */
4185: /* lli=log(mytinydouble); */
4186: /* else */
4187: /* lli=log(out[s1][s2] - savm[s1][s2]); */
4188: /* #endif */
1.226 brouard 4189: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4190:
1.226 brouard 4191: } else if ( s2==-1 ) { /* alive */
4192: for (j=1,survp=0. ; j<=nlstate; j++)
4193: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4194: /*survp += out[s1][j]; */
4195: lli= log(survp);
4196: }
1.336 brouard 4197: /* else if (s2==-4) { */
4198: /* for (j=3,survp=0. ; j<=nlstate; j++) */
4199: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4200: /* lli= log(survp); */
4201: /* } */
4202: /* else if (s2==-5) { */
4203: /* for (j=1,survp=0. ; j<=2; j++) */
4204: /* survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j]; */
4205: /* lli= log(survp); */
4206: /* } */
1.226 brouard 4207: else{
4208: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4209: /* lli= (savm[s1][s2]>(double)1.e-8 ?log((1.+bbh)*out[s1][s2]- bbh*(savm[s1][s2])):log((1.+bbh)*out[s1][s2]));*/ /* linear interpolation */
4210: }
4211: /*lli=(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]);*/
4212: /*if(lli ==000.0)*/
1.340 brouard 4213: /* printf("num[i], i=%d, bbh= %f lli=%f savm=%f out=%f %d\n",bbh,lli,savm[s1][s2], out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]],i); */
1.226 brouard 4214: ipmx +=1;
4215: sw += weight[i];
4216: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4217: /* if (lli < log(mytinydouble)){ */
4218: /* printf("Close to inf lli = %.10lf < %.10lf i= %d mi= %d, s[%d][i]=%d s1=%d s2=%d\n", lli,log(mytinydouble), i, mi,mw[mi][i], s[mw[mi][i]][i], s1,s2); */
4219: /* fprintf(ficlog,"Close to inf lli = %.10lf i= %d mi= %d, s[mw[mi][i]][i]=%d\n", lli, i, mi,s[mw[mi][i]][i]); */
4220: /* } */
4221: } /* end of wave */
4222: } /* end of individual */
4223: } else if(mle==2){
4224: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.319 brouard 4225: ioffset=2+nagesqr ;
4226: for (k=1; k<=ncovf;k++)
4227: cov[ioffset+TvarFind[k]]=covar[Tvar[TvarFind[k]]][i];
1.226 brouard 4228: for(mi=1; mi<= wav[i]-1; mi++){
1.319 brouard 4229: for(k=1; k <= ncovv ; k++){
1.341 brouard 4230: cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.319 brouard 4231: }
1.226 brouard 4232: for (ii=1;ii<=nlstate+ndeath;ii++)
4233: for (j=1;j<=nlstate+ndeath;j++){
4234: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4235: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4236: }
4237: for(d=0; d<=dh[mi][i]; d++){
4238: newm=savm;
4239: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4240: cov[2]=agexact;
4241: if(nagesqr==1)
4242: cov[3]= agexact*agexact;
4243: for (kk=1; kk<=cptcovage;kk++) {
4244: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4245: }
4246: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4247: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4248: savm=oldm;
4249: oldm=newm;
4250: } /* end mult */
4251:
4252: s1=s[mw[mi][i]][i];
4253: s2=s[mw[mi+1][i]][i];
4254: bbh=(double)bh[mi][i]/(double)stepm;
4255: lli= (savm[s1][s2]>(double)1.e-8 ?log((1.+bbh)*out[s1][s2]- bbh*(savm[s1][s2])):log((1.+bbh)*out[s1][s2])); /* linear interpolation */
4256: ipmx +=1;
4257: sw += weight[i];
4258: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4259: } /* end of wave */
4260: } /* end of individual */
4261: } else if(mle==3){ /* exponential inter-extrapolation */
4262: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4263: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4264: for(mi=1; mi<= wav[i]-1; mi++){
4265: for (ii=1;ii<=nlstate+ndeath;ii++)
4266: for (j=1;j<=nlstate+ndeath;j++){
4267: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4268: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4269: }
4270: for(d=0; d<dh[mi][i]; d++){
4271: newm=savm;
4272: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4273: cov[2]=agexact;
4274: if(nagesqr==1)
4275: cov[3]= agexact*agexact;
4276: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4277: if(!FixedV[Tvar[Tage[kk]]])
4278: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4279: else
1.341 brouard 4280: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.226 brouard 4281: }
4282: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4283: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4284: savm=oldm;
4285: oldm=newm;
4286: } /* end mult */
4287:
4288: s1=s[mw[mi][i]][i];
4289: s2=s[mw[mi+1][i]][i];
4290: bbh=(double)bh[mi][i]/(double)stepm;
4291: lli= (savm[s1][s2]>1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2])); /* exponential inter-extrapolation */
4292: ipmx +=1;
4293: sw += weight[i];
4294: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4295: } /* end of wave */
4296: } /* end of individual */
4297: }else if (mle==4){ /* ml=4 no inter-extrapolation */
4298: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4299: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4300: for(mi=1; mi<= wav[i]-1; mi++){
4301: for (ii=1;ii<=nlstate+ndeath;ii++)
4302: for (j=1;j<=nlstate+ndeath;j++){
4303: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4304: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4305: }
4306: for(d=0; d<dh[mi][i]; d++){
4307: newm=savm;
4308: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4309: cov[2]=agexact;
4310: if(nagesqr==1)
4311: cov[3]= agexact*agexact;
4312: for (kk=1; kk<=cptcovage;kk++) {
4313: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact;
4314: }
1.126 brouard 4315:
1.226 brouard 4316: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4317: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4318: savm=oldm;
4319: oldm=newm;
4320: } /* end mult */
4321:
4322: s1=s[mw[mi][i]][i];
4323: s2=s[mw[mi+1][i]][i];
4324: if( s2 > nlstate){
4325: lli=log(out[s1][s2] - savm[s1][s2]);
4326: } else if ( s2==-1 ) { /* alive */
4327: for (j=1,survp=0. ; j<=nlstate; j++)
4328: survp += out[s1][j];
4329: lli= log(survp);
4330: }else{
4331: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4332: }
4333: ipmx +=1;
4334: sw += weight[i];
4335: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.343 brouard 4336: /* printf("num[i]=%09ld, i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",num[i],i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.226 brouard 4337: } /* end of wave */
4338: } /* end of individual */
4339: }else{ /* ml=5 no inter-extrapolation no jackson =0.8a */
4340: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
4341: for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i];
4342: for(mi=1; mi<= wav[i]-1; mi++){
4343: for (ii=1;ii<=nlstate+ndeath;ii++)
4344: for (j=1;j<=nlstate+ndeath;j++){
4345: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4346: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4347: }
4348: for(d=0; d<dh[mi][i]; d++){
4349: newm=savm;
4350: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM;
4351: cov[2]=agexact;
4352: if(nagesqr==1)
4353: cov[3]= agexact*agexact;
4354: for (kk=1; kk<=cptcovage;kk++) {
1.340 brouard 4355: if(!FixedV[Tvar[Tage[kk]]])
4356: cov[Tage[kk]+2+nagesqr]=covar[Tvar[Tage[kk]]][i]*agexact; /* Tage[kk] gives the data-covariate associated with age */
4357: else
1.341 brouard 4358: cov[Tage[kk]+2+nagesqr]=cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]*agexact; /* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.226 brouard 4359: }
1.126 brouard 4360:
1.226 brouard 4361: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4362: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4363: savm=oldm;
4364: oldm=newm;
4365: } /* end mult */
4366:
4367: s1=s[mw[mi][i]][i];
4368: s2=s[mw[mi+1][i]][i];
4369: lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]); /* Original formula */
4370: ipmx +=1;
4371: sw += weight[i];
4372: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
4373: /*printf("i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],out[s1][s2],savm[s1][s2]);*/
4374: } /* end of wave */
4375: } /* end of individual */
4376: } /* End of if */
4377: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
4378: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
4379: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4380: return -l;
1.126 brouard 4381: }
4382:
4383: /*************** log-likelihood *************/
4384: double funcone( double *x)
4385: {
1.228 brouard 4386: /* Same as func but slower because of a lot of printf and if */
1.349 brouard 4387: int i, ii, j, k, mi, d, kk, kv=0, kf=0;
1.228 brouard 4388: int ioffset=0;
1.339 brouard 4389: int ipos=0,iposold=0,ncovv=0;
4390:
1.340 brouard 4391: double cotvarv, cotvarvold;
1.131 brouard 4392: double l, ll[NLSTATEMAX+1], cov[NCOVMAX+1];
1.126 brouard 4393: double **out;
4394: double lli; /* Individual log likelihood */
4395: double llt;
4396: int s1, s2;
1.228 brouard 4397: int iv=0, iqv=0, itv=0, iqtv=0 ; /* Index of varying covariate, fixed quantitative cov, time varying covariate, quantitative time varying covariate */
4398:
1.126 brouard 4399: double bbh, survp;
1.187 brouard 4400: double agexact;
1.214 brouard 4401: double agebegin, ageend;
1.126 brouard 4402: /*extern weight */
4403: /* We are differentiating ll according to initial status */
4404: /* for (i=1;i<=npar;i++) printf("%f ", x[i]);*/
4405: /*for(i=1;i<imx;i++)
4406: printf(" %d\n",s[4][i]);
4407: */
4408: cov[1]=1.;
4409:
4410: for(k=1; k<=nlstate; k++) ll[k]=0.;
1.224 brouard 4411: ioffset=0;
4412: for (i=1,ipmx=0, sw=0.; i<=imx; i++){
1.336 brouard 4413: /* Computes the values of the ncovmodel covariates of the model
4414: depending if the covariates are fixed or varying (age dependent) and stores them in cov[]
4415: Then computes with function pmij which return a matrix p[i][j] giving the elementary probability
4416: to be observed in j being in i according to the model.
4417: */
1.243 brouard 4418: /* ioffset=2+nagesqr+cptcovage; */
4419: ioffset=2+nagesqr;
1.232 brouard 4420: /* Fixed */
1.224 brouard 4421: /* for (k=1; k<=cptcovn;k++) cov[2+nagesqr+k]=covar[Tvar[k]][i]; */
1.232 brouard 4422: /* for (k=1; k<=ncoveff;k++){ /\* Simple and product fixed Dummy covariates without age* products *\/ */
1.349 brouard 4423: for (kf=1; kf<=ncovf;kf++){ /* V2 + V3 + V4 Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
1.339 brouard 4424: /* printf("Debug3 TvarFind[%d]=%d",kf, TvarFind[kf]); */
4425: /* printf(" Tvar[TvarFind[kf]]=%d", Tvar[TvarFind[kf]]); */
4426: /* printf(" i=%d covar[Tvar[TvarFind[kf]]][i]=%f\n",i,covar[Tvar[TvarFind[kf]]][i]); */
1.335 brouard 4427: cov[ioffset+TvarFind[kf]]=covar[Tvar[TvarFind[kf]]][i];/* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V1 is fixed (k=6)*/
1.232 brouard 4428: /* cov[ioffset+TvarFind[1]]=covar[Tvar[TvarFind[1]]][i]; */
4429: /* cov[2+6]=covar[Tvar[6]][i]; */
4430: /* cov[2+6]=covar[2][i]; V2 */
4431: /* cov[TvarFind[2]]=covar[Tvar[TvarFind[2]]][i]; */
4432: /* cov[2+7]=covar[Tvar[7]][i]; */
4433: /* cov[2+7]=covar[7][i]; V7=V1*V2 */
4434: /* cov[TvarFind[3]]=covar[Tvar[TvarFind[3]]][i]; */
4435: /* cov[2+9]=covar[Tvar[9]][i]; */
4436: /* cov[2+9]=covar[1][i]; V1 */
1.225 brouard 4437: }
1.336 brouard 4438: /* In model V2+V1*V4+age*V3+V3*V2 Tvar[1] is V2, Tvar[2=V1*V4]
4439: is 5, Tvar[3=age*V3] should not be computed because of age Tvar[4=V3*V2]=6
4440: has been calculated etc */
4441: /* For an individual i, wav[i] gives the number of effective waves */
4442: /* We compute the contribution to Likelihood of each effective transition
4443: mw[mi][i] is real wave of the mi th effectve wave */
4444: /* Then statuses are computed at each begin and end of an effective wave s1=s[ mw[mi][i] ][i];
4445: s2=s[mw[mi+1][i]][i];
1.341 brouard 4446: And the iv th varying covariate in the DATA is the cotvar[mw[mi+1][i]][ncovcol+nqv+iv][i]
1.336 brouard 4447: */
4448: /* This part may be useless now because everythin should be in covar */
1.232 brouard 4449: /* for (k=1; k<=nqfveff;k++){ /\* Simple and product fixed Quantitative covariates without age* products *\/ */
4450: /* cov[++ioffset]=coqvar[TvarFQ[k]][i];/\* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, only V2 and V1*V2 is fixed (k=6 and 7?)*\/ */
4451: /* } */
1.231 brouard 4452: /* for(iqv=1; iqv <= nqfveff; iqv++){ /\* Quantitative fixed covariates *\/ */
4453: /* cov[++ioffset]=coqvar[Tvar[iqv]][i]; /\* Only V2 k=6 and V1*V2 7 *\/ */
4454: /* } */
1.225 brouard 4455:
1.233 brouard 4456:
4457: for(mi=1; mi<= wav[i]-1; mi++){ /* Varying with waves */
1.339 brouard 4458: /* Wave varying (but not age varying) *//* V1+V3+age*V1+age*V3+V1*V3 with V4 tv and V5 tvq k= 1 to 5 and extra at V(5+1)=6 for V1*V3 */
4459: /* for(k=1; k <= ncovv ; k++){ /\* Varying covariates (single and product but no age )*\/ */
4460: /* /\* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]][i]; *\/ */
4461: /* cov[ioffset+TvarVind[k]]=cotvar[mw[mi][i]][Tvar[TvarVind[k]]-ncovcol-nqv][i]; */
4462: /* } */
4463:
4464: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
4465: /* model V1+V3+age*V1+age*V3+V1*V3 */
4466: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
4467: /* TvarVV[1]=V3 (first time varying in the model equation, TvarVV[2]=V1 (in V1*V3) TvarVV[3]=3(V3) */
4468: /* We need the position of the time varying or product in the model */
4469: /* TvarVVind={2,5,5}, for V3 at position 2 and then the product V1*V3 is decomposed into V1 and V3 but at same position 5 */
4470: /* TvarVV gives the variable name */
1.340 brouard 4471: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
4472: * k= 1 2 3 4 5 6 7 8 9
4473: * varying 1 2 3 4 5
4474: * ncovv 1 2 3 4 5 6 7 8
1.343 brouard 4475: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
1.340 brouard 4476: * TvarVVind 2 3 7 7 8 8 9 9
4477: * TvarFind[k] 1 0 0 0 0 0 0 0 0
4478: */
1.345 brouard 4479: /* Other model ncovcol=5 nqv=0 ntv=3 nqtv=0 nlstate=3
1.349 brouard 4480: * V2 V3 V4 are fixed V6 V7 are timevarying so V8 and V5 are not in the model and product column will start at 9 Tvar[(v6*V2)6]=9
1.345 brouard 4481: * FixedV[ncovcol+qv+ntv+nqtv] V5
1.349 brouard 4482: * 3 V1 V2 V3 V4 V5 V6 V7 V8 V3*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4483: * 0 0 0 0 0 1 1 1 0, 0, 1,1, 1, 0, 1, 0, 1, 0, 1, 0}
4484: * 3 0 0 0 0 0 1 1 1 0, 1 1 1 1 1}
4485: * model= V2 + V3 + V4 + V6 + V7 + V6*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4486: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4487: * +age*V6*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4488: * model2= V2 + V3 + V4 + V6 + V7 + V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4489: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4490: * +age*V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4491: * model3= V2 + V3 + V4 + V6 + V7 + age*V3*V2 + V7*V2 + V6*V3 + V7*V3 + V6*V4 + V7*V4
4492: * +age*V2 +age*V3 +age*V4 +age*V6 + age*V7
4493: * +V3*V2 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4494: * kmodel 1 2 3 4 5 6 7 8 9 10 11
4495: * 12 13 14 15 16
4496: * 17 18 19 20 21
4497: * Tvar[kmodel] 2 3 4 6 7 9 10 11 12 13 14
4498: * 2 3 4 6 7
4499: * 9 11 12 13 14
4500: * cptcovage=5+5 total of covariates with age
4501: * Tage[cptcovage] age*V2=12 13 14 15 16
4502: *1 17 18 19 20 21 gives the position in model of covariates associated with age
4503: *3 Tage[cptcovage] age*V3*V2=6
4504: *3 age*V2=12 13 14 15 16
4505: *3 age*V6*V3=18 19 20 21
4506: * Tvar[Tage[cptcovage]] Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4507: * Tvar[17]age*V6*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4508: * 2 Tvar[17]age*V3*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4509: * 3 Tvar[Tage[cptcovage]] Tvar[6]=9 Tvar[12]=2 3 4 6 Tvar[16]=7(age*V7)
4510: * 3 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4511: * 3 Tage[cptcovage] age*V3*V2=6 age*V2=12 age*V3 13 14 15 16
4512: * age*V6*V3=18 19 20 21 gives the position in model of covariates associated with age
4513: * 3 Tvar[17]age*V3*V2=9 Tvar[18]age*V6*V3=11 age*V7*V3=12 age*V6*V4=13 Tvar[21]age*V7*V4=14
4514: * Tvar= {2, 3, 4, 6, 7,
4515: * 9, 10, 11, 12, 13, 14,
4516: * Tvar[12]=2, 3, 4, 6, 7,
4517: * Tvar[17]=9, 11, 12, 13, 14}
4518: * Typevar[1]@21 = {0, 0, 0, 0, 0,
4519: * 2, 2, 2, 2, 2, 2,
4520: * 3 3, 2, 2, 2, 2, 2,
4521: * 1, 1, 1, 1, 1,
4522: * 3, 3, 3, 3, 3}
4523: * 3 2, 3, 3, 3, 3}
4524: * p Tposprod[1]@21 {0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0, 1, 3, 4, 5, 6} Id of the prod at position k in the model
4525: * p Tprod[1]@21 {6, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4526: * 3 Tposprod[1]@21 {0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0, 1, 3, 4, 5, 6}
4527: * 3 Tprod[1]@21 {17, 7, 8, 9, 10, 11, 0 <repeats 15 times>}
4528: * cptcovprod=11 (6+5)
4529: * FixedV[Tvar[Tage[cptcovage]]]] FixedV[2]=0 FixedV[3]=0 0 1 (age*V7)Tvar[16]=1 FixedV[absolute] not [kmodel]
4530: * FixedV[Tvar[17]=FixedV[age*V6*V2]=FixedV[9]=1 1 1 1 1
4531: * 3 FixedV[Tvar[17]=FixedV[age*V3*V2]=FixedV[9]=0 [11]=1 1 1 1
4532: * FixedV[] V1=0 V2=0 V3=0 v4=0 V5=0 V6=1 V7=1 v8=1 OK then model dependent
4533: * 9=1 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4534: * 3 9=0 [V7*V2]=[10]=1 11=1 12=1 13=1 14=1
4535: * cptcovdageprod=5 for gnuplot printing
4536: * cptcovprodvage=6
4537: * ncova=15 1 2 3 4 5
4538: * 6 7 8 9 10 11 12 13 14 15
4539: * TvarA 2 3 4 6 7
4540: * 6 2 6 7 7 3 6 4 7 4
4541: * TvaAind 12 12 13 13 14 14 15 15 16 16
1.345 brouard 4542: * ncovf 1 2 3
1.349 brouard 4543: * V6 V7 V6*V2 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4544: * ncovvt=14 1 2 3 4 5 6 7 8 9 10 11 12 13 14
4545: * TvarVV[1]@14 = itv {V6=6, 7, V6*V2=6, 2, 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4546: * TvarVVind[1]@14= {4, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11}
4547: * 3 ncovvt=12 V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4
4548: * 3 TvarVV[1]@12 = itv {6, 7, V7*V2=7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
4549: * 3 1 2 3 4 5 6 7 8 9 10 11 12
4550: * TvarVVind[1]@12= {V6 is in k=4, 5, 7,(4isV2)=7, 8, 8, 9, 9, 10,10, 11,11}TvarVVind[12]=k=11
4551: * TvarV 6, 7, 9, 10, 11, 12, 13, 14
4552: * 3 cptcovprodvage=6
4553: * 3 ncovta=15 +age*V3*V2+age*V2+agev3+ageV4 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4554: * 3 TvarAVVA[1]@15= itva 3 2 2 3 4 6 7 6 3 7 3 6 4 7 4
4555: * 3 ncovta 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1.354 ! brouard 4556: *?TvarAVVAind[1]@15= V3 is in k=2 1 1 2 3 4 5 4,2 5,2, 4,3 5 3}TvarVVAind[]
1.349 brouard 4557: * TvarAVVAind[1]@15= V3 is in k=6 6 12 13 14 15 16 18 18 19,19, 20,20 21,21}TvarVVAind[]
4558: * 3 ncovvta=10 +age*V6 + age*V7 + age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4
4559: * 3 we want to compute =cotvar[mw[mi][i]][TvarVVA[ncovva]][i] at position TvarVVAind[ncovva]
4560: * 3 TvarVVA[1]@10= itva 6 7 6 3 7 3 6 4 7 4
4561: * 3 ncovva 1 2 3 4 5 6 7 8 9 10
4562: * TvarVVAind[1]@10= V6 is in k=4 5 8,8 9, 9, 10,10 11 11}TvarVVAind[]
4563: * TvarVVAind[1]@10= 15 16 18,18 19,19, 20,20 21 21}TvarVVAind[]
4564: * TvarVA V3*V2=6 6 , 1, 2, 11, 12, 13, 14
1.345 brouard 4565: * TvarFind[1]@14= {1, 2, 3, 0 <repeats 12 times>}
1.349 brouard 4566: * Tvar[1]@21= {2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14,
4567: * 2, 3, 4, 6, 7,
4568: * 6, 8, 9, 10, 11}
1.345 brouard 4569: * TvarFind[itv] 0 0 0
4570: * FixedV[itv] 1 1 1 0 1 0 1 0 1 0 0
1.354 ! brouard 4571: *? FixedV[itv] 1 1 1 0 1 0 1 0 1 0 1 0 1 0
1.345 brouard 4572: * Tvar[TvarFind[ncovf]]=[1]=2 [2]=3 [4]=4
4573: * Tvar[TvarFind[itv]] [0]=? ?ncovv 1 à ncovvt]
4574: * Not a fixed cotvar[mw][itv][i] 6 7 6 2 7, 2, 6, 3, 7, 3, 6, 4, 7, 4}
1.349 brouard 4575: * fixed covar[itv] [6] [7] [6][2]
1.345 brouard 4576: */
4577:
1.349 brouard 4578: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* V6 V7 V7*V2 V6*V3 V7*V3 V6*V4 V7*V4 Time varying covariates (single and extended product but no age) including individual from products, product is computed dynamically */
4579: itv=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, or fixed covariate of a varying product after exploding product Vn*Vm into Vn and then Vm */
1.340 brouard 4580: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
1.345 brouard 4581: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4582: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
1.354 ! brouard 4583: /* printf("DEBUG ncovv=%d, Varying TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.345 brouard 4584: cotvarv=cotvar[mw[mi][i]][TvarVV[ncovv]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
1.354 ! brouard 4585: /* printf("DEBUG Varying cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 4586: }else{ /* fixed covariate */
1.345 brouard 4587: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
1.354 ! brouard 4588: /* printf("DEBUG ncovv=%d, Fixed TvarVV[ncovv]=%d\n",ncovv, TvarVV[ncovv]); */
1.349 brouard 4589: cotvarv=covar[itv][i]; /* Good: In V6*V3, 3 is fixed at position of the data */
1.354 ! brouard 4590: /* printf("DEBUG Fixed cov[ioffset+ipos=%d]=%g \n",ioffset+ipos,cotvarv); */
1.340 brouard 4591: }
1.339 brouard 4592: if(ipos!=iposold){ /* Not a product or first of a product */
1.340 brouard 4593: cotvarvold=cotvarv;
4594: }else{ /* A second product */
4595: cotvarv=cotvarv*cotvarvold;
1.339 brouard 4596: }
4597: iposold=ipos;
1.340 brouard 4598: cov[ioffset+ipos]=cotvarv;
1.354 ! brouard 4599: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
1.339 brouard 4600: /* For products */
4601: }
4602: /* for(itv=1; itv <= ntveff; itv++){ /\* Varying dummy covariates single *\/ */
4603: /* iv=TvarVDind[itv]; /\* iv, position in the model equation of time varying covariate itv *\/ */
4604: /* /\* "V1+V3+age*V1+age*V3+V1*V3" with V3 time varying *\/ */
4605: /* /\* 1 2 3 4 5 *\/ */
4606: /* /\*itv 1 *\/ */
4607: /* /\* TvarVInd[1]= 2 *\/ */
4608: /* /\* iv= Tvar[Tmodelind[itv]]-ncovcol-nqv; /\\* Counting the # varying covariate from 1 to ntveff *\\/ *\/ */
4609: /* /\* iv= Tvar[Tmodelind[ioffset-2-nagesqr-cptcovage+itv]]-ncovcol-nqv; *\/ */
4610: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][iv][i]; *\/ */
4611: /* /\* k=ioffset-2-nagesqr-cptcovage+itv; /\\* position in simple model *\\/ *\/ */
4612: /* /\* cov[ioffset+iv]=cotvar[mw[mi][i]][TmodelInvind[itv]][i]; *\/ */
4613: /* cov[ioffset+iv]=cotvar[mw[mi][i]][itv][i]; */
4614: /* /\* printf(" i=%d,mi=%d,itv=%d,TmodelInvind[itv]=%d,cotvar[mw[mi][i]][itv][i]=%f\n", i, mi, itv, TvarVDind[itv],cotvar[mw[mi][i]][itv][i]); *\/ */
4615: /* } */
1.232 brouard 4616: /* for(iqtv=1; iqtv <= nqtveff; iqtv++){ /\* Varying quantitatives covariates *\/ */
1.242 brouard 4617: /* iv=TmodelInvQind[iqtv]; /\* Counting the # varying covariate from 1 to ntveff *\/ */
4618: /* /\* printf(" i=%d,mi=%d,iqtv=%d,TmodelInvQind[iqtv]=%d,cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]=%f\n", i, mi, iqtv, TmodelInvQind[iqtv],cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]); *\/ */
4619: /* cov[ioffset+ntveff+iqtv]=cotqvar[mw[mi][i]][TmodelInvQind[iqtv]][i]; */
1.232 brouard 4620: /* } */
1.126 brouard 4621: for (ii=1;ii<=nlstate+ndeath;ii++)
1.242 brouard 4622: for (j=1;j<=nlstate+ndeath;j++){
4623: oldm[ii][j]=(ii==j ? 1.0 : 0.0);
4624: savm[ii][j]=(ii==j ? 1.0 : 0.0);
4625: }
1.214 brouard 4626:
4627: agebegin=agev[mw[mi][i]][i]; /* Age at beginning of effective wave */
4628: ageend=agev[mw[mi][i]][i] + (dh[mi][i])*stepm/YEARM; /* Age at end of effective wave and at the end of transition */
4629: for(d=0; d<dh[mi][i]; d++){ /* Delay between two effective waves */
1.247 brouard 4630: /* for(d=0; d<=0; d++){ /\* Delay between two effective waves Only one matrix to speed up*\/ */
1.242 brouard 4631: /*dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
4632: and mw[mi+1][i]. dh depends on stepm.*/
4633: newm=savm;
1.247 brouard 4634: agexact=agev[mw[mi][i]][i]+d*stepm/YEARM; /* Here d is needed */
1.242 brouard 4635: cov[2]=agexact;
4636: if(nagesqr==1)
4637: cov[3]= agexact*agexact;
1.349 brouard 4638: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4639: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4640: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4641: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4642: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4643: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4644: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4645: }else{ /* fixed covariate */
4646: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4647: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4648: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4649: }
4650: if(ipos!=iposold){ /* Not a product or first of a product */
4651: cotvarvold=cotvarv;
4652: }else{ /* A second product */
4653: /* printf("DEBUG * \n"); */
4654: cotvarv=cotvarv*cotvarvold;
4655: }
4656: iposold=ipos;
4657: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4658: cov[ioffset+ipos]=cotvarv*agexact;
4659: /* For products */
1.242 brouard 4660: }
1.349 brouard 4661:
1.242 brouard 4662: /* printf("i=%d,mi=%d,d=%d,mw[mi][i]=%d\n",i, mi,d,mw[mi][i]); */
4663: /* savm=pmij(pmmij,cov,ncovmodel,x,nlstate); */
4664: out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath,
4665: 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate));
4666: /* out=matprod2(newm,oldm,1,nlstate+ndeath,1,nlstate+ndeath, */
4667: /* 1,nlstate+ndeath,pmij(pmmij,cov,ncovmodel,x,nlstate)); */
4668: savm=oldm;
4669: oldm=newm;
1.126 brouard 4670: } /* end mult */
1.336 brouard 4671: /*lli=log(out[s[mw[mi][i]][i]][s[mw[mi+1][i]][i]]);*/ /* Original formula */
4672: /* But now since version 0.9 we anticipate for bias at large stepm.
4673: * If stepm is larger than one month (smallest stepm) and if the exact delay
4674: * (in months) between two waves is not a multiple of stepm, we rounded to
4675: * the nearest (and in case of equal distance, to the lowest) interval but now
4676: * we keep into memory the bias bh[mi][i] and also the previous matrix product
4677: * (i.e to dh[mi][i]-1) saved in 'savm'. Then we inter(extra)polate the
4678: * probability in order to take into account the bias as a fraction of the way
4679: * from savm to out if bh is negative or even beyond if bh is positive. bh varies
4680: * -stepm/2 to stepm/2 .
4681: * For stepm=1 the results are the same as for previous versions of Imach.
4682: * For stepm > 1 the results are less biased than in previous versions.
4683: */
1.126 brouard 4684: s1=s[mw[mi][i]][i];
4685: s2=s[mw[mi+1][i]][i];
1.217 brouard 4686: /* if(s2==-1){ */
1.268 brouard 4687: /* printf(" ERROR s1=%d, s2=%d i=%d \n", s1, s2, i); */
1.217 brouard 4688: /* /\* exit(1); *\/ */
4689: /* } */
1.126 brouard 4690: bbh=(double)bh[mi][i]/(double)stepm;
4691: /* bias is positive if real duration
4692: * is higher than the multiple of stepm and negative otherwise.
4693: */
4694: if( s2 > nlstate && (mle <5) ){ /* Jackson */
1.242 brouard 4695: lli=log(out[s1][s2] - savm[s1][s2]);
1.216 brouard 4696: } else if ( s2==-1 ) { /* alive */
1.242 brouard 4697: for (j=1,survp=0. ; j<=nlstate; j++)
4698: survp += (1.+bbh)*out[s1][j]- bbh*savm[s1][j];
4699: lli= log(survp);
1.126 brouard 4700: }else if (mle==1){
1.242 brouard 4701: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
1.126 brouard 4702: } else if(mle==2){
1.242 brouard 4703: lli= (savm[s1][s2]>(double)1.e-8 ?log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]):log((1.+bbh)*out[s1][s2])); /* linear interpolation */
1.126 brouard 4704: } else if(mle==3){ /* exponential inter-extrapolation */
1.242 brouard 4705: lli= (savm[s1][s2]>(double)1.e-8 ?(1.+bbh)*log(out[s1][s2])- bbh*log(savm[s1][s2]):log((1.+bbh)*out[s1][s2])); /* exponential inter-extrapolation */
1.126 brouard 4706: } else if (mle==4){ /* mle=4 no inter-extrapolation */
1.242 brouard 4707: lli=log(out[s1][s2]); /* Original formula */
1.136 brouard 4708: } else{ /* mle=0 back to 1 */
1.242 brouard 4709: lli= log((1.+bbh)*out[s1][s2]- bbh*savm[s1][s2]); /* linear interpolation */
4710: /*lli=log(out[s1][s2]); */ /* Original formula */
1.126 brouard 4711: } /* End of if */
4712: ipmx +=1;
4713: sw += weight[i];
4714: ll[s[mw[mi][i]][i]] += 2*weight[i]*lli;
1.342 brouard 4715: /* Printing covariates values for each contribution for checking */
1.343 brouard 4716: /* printf("num[i]=%09ld, i=%6d s1=%1d s2=%1d mi=%1d mw=%1d dh=%3d prob=%10.6f w=%6.4f out=%10.6f sav=%10.6f\n",num[i],i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.126 brouard 4717: if(globpr){
1.246 brouard 4718: fprintf(ficresilk,"%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\
1.126 brouard 4719: %11.6f %11.6f %11.6f ", \
1.242 brouard 4720: num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw,
1.268 brouard 4721: 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2]));
1.343 brouard 4722: /* printf("%09ld %6.1f %6.1f %6d %2d %2d %2d %2d %3d %15.6f %8.4f %8.3f\ */
4723: /* %11.6f %11.6f %11.6f ", \ */
4724: /* num[i], agebegin, ageend, i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],weight[i]*gipmx/gsw, */
4725: /* 2*weight[i]*lli,(s2==-1? -1: out[s1][s2]),(s2==-1? -1: savm[s1][s2])); */
1.242 brouard 4726: for(k=1,llt=0.,l=0.; k<=nlstate; k++){
4727: llt +=ll[k]*gipmx/gsw;
4728: fprintf(ficresilk," %10.6f",-ll[k]*gipmx/gsw);
1.335 brouard 4729: /* printf(" %10.6f",-ll[k]*gipmx/gsw); */
1.242 brouard 4730: }
1.343 brouard 4731: fprintf(ficresilk," %10.6f ", -llt);
1.335 brouard 4732: /* printf(" %10.6f\n", -llt); */
1.342 brouard 4733: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
1.343 brouard 4734: /* fprintf(ficresilk,"%09ld ", num[i]); */ /* not necessary */
4735: for (kf=1; kf<=ncovf;kf++){ /* Simple and product fixed covariates without age* products *//* Missing values are set to -1 but should be dropped */
4736: fprintf(ficresilk," %g",covar[Tvar[TvarFind[kf]]][i]);
4737: }
4738: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Varying covariates (single and product but no age) including individual from products */
4739: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4740: if(ipos!=iposold){ /* Not a product or first of a product */
4741: fprintf(ficresilk," %g",cov[ioffset+ipos]);
4742: /* printf(" %g",cov[ioffset+ipos]); */
4743: }else{
4744: fprintf(ficresilk,"*");
4745: /* printf("*"); */
1.342 brouard 4746: }
1.343 brouard 4747: iposold=ipos;
4748: }
1.349 brouard 4749: /* for (kk=1; kk<=cptcovage;kk++) { */
4750: /* if(!FixedV[Tvar[Tage[kk]]]){ */
4751: /* fprintf(ficresilk," %g*age",covar[Tvar[Tage[kk]]][i]); */
4752: /* /\* printf(" %g*age",covar[Tvar[Tage[kk]]][i]); *\/ */
4753: /* }else{ */
4754: /* fprintf(ficresilk," %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4755: /* /\* printf(" %g*age",cotvar[mw[mi][i]][Tvar[Tage[kk]]][i]);/\\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\\/ *\/ */
4756: /* } */
4757: /* } */
4758: for(ncovva=1, iposold=0; ncovva <= ncovta ; ncovva++){ /* Time varying covariates with age including individual from products, product is computed dynamically */
4759: itv=TvarAVVA[ncovva]; /* TvarVV={3, 1, 3} gives the name of each varying covariate, exploding product Vn*Vm into Vn and then Vm */
4760: ipos=TvarAVVAind[ncovva]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate*/
4761: /* if(TvarFind[itv]==0){ /\* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv *\/ */
4762: if(FixedV[itv]!=0){ /* Not a fixed covariate? Could be a fixed covariate of a product with a higher than ncovcol+nqv, itv */
4763: /* printf("DEBUG ncovva=%d, Varying TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4764: cotvarv=cotvar[mw[mi][i]][TvarAVVA[ncovva]][i]; /* because cotvar starts now at first ncovcol+nqv+ntv+nqtv (1 to nqtv) */
4765: }else{ /* fixed covariate */
4766: /* cotvarv=covar[Tvar[TvarFind[itv]]][i]; /\* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model *\/ */
4767: /* printf("DEBUG ncovva=%d, Fixed TvarAVVA[ncovva]=%d\n", ncovva, TvarAVVA[ncovva]); */
4768: cotvarv=covar[itv][i]; /* Error: TvarFind gives the name, that is the true column of fixed covariates, but Tvar of the model */
4769: }
4770: if(ipos!=iposold){ /* Not a product or first of a product */
4771: cotvarvold=cotvarv;
4772: }else{ /* A second product */
4773: /* printf("DEBUG * \n"); */
4774: cotvarv=cotvarv*cotvarvold;
1.342 brouard 4775: }
1.349 brouard 4776: cotvarv=cotvarv*agexact;
4777: fprintf(ficresilk," %g*age",cotvarv);
4778: iposold=ipos;
4779: /* printf("DEBUG Product cov[ioffset+ipos=%d] \n",ioffset+ipos); */
4780: cov[ioffset+ipos]=cotvarv;
4781: /* For products */
1.343 brouard 4782: }
4783: /* printf("\n"); */
1.342 brouard 4784: /* } /\* End debugILK *\/ */
4785: fprintf(ficresilk,"\n");
4786: } /* End if globpr */
1.335 brouard 4787: } /* end of wave */
4788: } /* end of individual */
4789: for(k=1,l=0.; k<=nlstate; k++) l += ll[k];
1.232 brouard 4790: /* printf("l1=%f l2=%f ",ll[1],ll[2]); */
1.335 brouard 4791: l= l*ipmx/sw; /* To get the same order of magnitude as if weight=1 for every body */
4792: if(globpr==0){ /* First time we count the contributions and weights */
4793: gipmx=ipmx;
4794: gsw=sw;
4795: }
1.343 brouard 4796: return -l;
1.126 brouard 4797: }
4798:
4799:
4800: /*************** function likelione ***********/
1.292 brouard 4801: void likelione(FILE *ficres,double p[], int npar, int nlstate, int *globpri, long *ipmx, double *sw, double *fretone, double (*func)(double []))
1.126 brouard 4802: {
4803: /* This routine should help understanding what is done with
4804: the selection of individuals/waves and
4805: to check the exact contribution to the likelihood.
4806: Plotting could be done.
1.342 brouard 4807: */
4808: void pstamp(FILE *ficres);
1.343 brouard 4809: int k, kf, kk, kvar, ncovv, iposold, ipos;
1.126 brouard 4810:
4811: if(*globpri !=0){ /* Just counts and sums, no printings */
1.201 brouard 4812: strcpy(fileresilk,"ILK_");
1.202 brouard 4813: strcat(fileresilk,fileresu);
1.126 brouard 4814: if((ficresilk=fopen(fileresilk,"w"))==NULL) {
4815: printf("Problem with resultfile: %s\n", fileresilk);
4816: fprintf(ficlog,"Problem with resultfile: %s\n", fileresilk);
4817: }
1.342 brouard 4818: pstamp(ficresilk);fprintf(ficresilk,"# model=1+age+%s\n",model);
1.214 brouard 4819: fprintf(ficresilk, "#individual(line's_record) count ageb ageend s1 s2 wave# effective_wave# number_of_matrices_product pij weight weight/gpw -2ln(pij)*weight 0pij_x 0pij_(x-stepm) cumulating_loglikeli_by_health_state(reweighted=-2ll*weightXnumber_of_contribs/sum_of_weights) and_total\n");
4820: fprintf(ficresilk, "#num_i ageb agend i s1 s2 mi mw dh likeli weight %%weight 2wlli out sav ");
1.126 brouard 4821: /* i,s1,s2,mi,mw[mi][i],dh[mi][i],exp(lli),weight[i],2*weight[i]*lli,out[s1][s2],savm[s1][s2]); */
4822: for(k=1; k<=nlstate; k++)
4823: fprintf(ficresilk," -2*gipw/gsw*weight*ll[%d]++",k);
1.342 brouard 4824: fprintf(ficresilk," -2*gipw/gsw*weight*ll(total) ");
4825:
4826: /* if(debugILK){ /\* debugILK is set by a #d in a comment line *\/ */
4827: for(kf=1;kf <= ncovf; kf++){
4828: fprintf(ficresilk,"V%d",Tvar[TvarFind[kf]]);
4829: /* printf("V%d",Tvar[TvarFind[kf]]); */
4830: }
4831: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){
1.343 brouard 4832: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
1.342 brouard 4833: if(ipos!=iposold){ /* Not a product or first of a product */
4834: /* printf(" %d",ipos); */
4835: fprintf(ficresilk," V%d",TvarVV[ncovv]);
4836: }else{
4837: /* printf("*"); */
4838: fprintf(ficresilk,"*");
1.343 brouard 4839: }
1.342 brouard 4840: iposold=ipos;
4841: }
4842: for (kk=1; kk<=cptcovage;kk++) {
4843: if(!FixedV[Tvar[Tage[kk]]]){
4844: /* printf(" %d*age(Fixed)",Tvar[Tage[kk]]); */
4845: fprintf(ficresilk," %d*age(Fixed)",Tvar[Tage[kk]]);
4846: }else{
4847: fprintf(ficresilk," %d*age(Varying)",Tvar[Tage[kk]]);/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
4848: /* printf(" %d*age(Varying)",Tvar[Tage[kk]]);/\* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) *\/ */
4849: }
4850: }
4851: /* } /\* End if debugILK *\/ */
4852: /* printf("\n"); */
4853: fprintf(ficresilk,"\n");
4854: } /* End glogpri */
1.126 brouard 4855:
1.292 brouard 4856: *fretone=(*func)(p);
1.126 brouard 4857: if(*globpri !=0){
4858: fclose(ficresilk);
1.205 brouard 4859: if (mle ==0)
4860: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with initial parameters and mle = %d.",mle);
4861: else if(mle >=1)
4862: fprintf(fichtm,"\n<br>File of contributions to the likelihood computed with optimized parameters mle = %d.",mle);
4863: fprintf(fichtm," You should at least run with mle >= 1 to get starting values corresponding to the optimized parameters in order to visualize the real contribution of each individual/wave: <a href=\"%s\">%s</a><br>\n",subdirf(fileresilk),subdirf(fileresilk));
1.274 brouard 4864: fprintf(fichtm,"\n<br>Equation of the model: <b>model=1+age+%s</b><br>\n",model);
1.208 brouard 4865:
1.207 brouard 4866: fprintf(fichtm,"<br>- The function drawn is -2Log(L) in Log scale: by state of origin <a href=\"%s-ori.png\">%s-ori.png</a><br> \
1.343 brouard 4867: <img src=\"%s-ori.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
1.207 brouard 4868: fprintf(fichtm,"<br>- and by state of destination <a href=\"%s-dest.png\">%s-dest.png</a><br> \
1.343 brouard 4869: <img src=\"%s-dest.png\">\n",subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"),subdirf2(optionfilefiname,"ILK_"));
4870:
4871: for (k=1; k<= nlstate ; k++) {
4872: fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j. Dot's sizes are related to corresponding weight: <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br>\n \
4873: <img src=\"%s-p%dj.png\">\n",k,k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k);
4874: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.350 brouard 4875: kvar=Tvar[TvarFind[kf]]; /* variable */
4876: fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j with colored covariate V%d. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): ",k,k,Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],Tvar[TvarFind[kf]]);
4877: fprintf(fichtm,"<a href=\"%s-p%dj-%d.png\">%s-p%dj-%d.png</a><br>",subdirf2(optionfilefiname,"ILK_"),k,kvar,subdirf2(optionfilefiname,"ILK_"),k,kvar);
4878: fprintf(fichtm,"<img src=\"%s-p%dj-%d.png\">",subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]);
1.343 brouard 4879: }
4880: for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /* Loop on the time varying extended covariates (with extension of Vn*Vm */
4881: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
4882: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
4883: /* printf("DebugILK fichtm ncovv=%d, kvar=TvarVV[ncovv]=V%d, ipos=TvarVVind[ncovv]=%d, Dummy[ipos]=%d, Typevar[ipos]=%d\n", ncovv,kvar,ipos,Dummy[ipos],Typevar[ipos]); */
4884: if(ipos!=iposold){ /* Not a product or first of a product */
4885: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
4886: /* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); */
4887: if(Dummy[ipos]==0 && Typevar[ipos]==0){ /* Only if dummy time varying: Dummy(0, 1=quant singor prod without age,2 dummy*age, 3quant*age) Typevar (0 single, 1=*age,2=Vn*vm) */
4888: fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j with colored time varying dummy covariate V%d. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \
4889: <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar);
4890: } /* End only for dummies time varying (single?) */
4891: }else{ /* Useless product */
4892: /* printf("*"); */
4893: /* fprintf(ficresilk,"*"); */
4894: }
4895: iposold=ipos;
4896: } /* For each time varying covariate */
4897: } /* End loop on states */
4898:
4899: /* if(debugILK){ */
4900: /* for(kf=1; kf <= ncovf; kf++){ /\* For each simple dummy covariate of the model *\/ */
4901: /* /\* kvar=Tvar[TvarFind[kf]]; *\/ /\* variable *\/ */
4902: /* for (k=1; k<= nlstate ; k++) { */
4903: /* fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j with colored covariate V%. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \ */
4904: /* <img src=\"%s-p%dj-%d.png\">",k,k,Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],Tvar[TvarFind[kf]],subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,Tvar[TvarFind[kf]]); */
4905: /* } */
4906: /* } */
4907: /* for(ncovv=1, iposold=0; ncovv <= ncovvt ; ncovv++){ /\* Loop on the time varying extended covariates (with extension of Vn*Vm *\/ */
4908: /* ipos=TvarVVind[ncovv]; /\* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate *\/ */
4909: /* kvar=TvarVV[ncovv]; /\* TvarVV={3, 1, 3} gives the name of each varying covariate *\/ */
4910: /* /\* printf("DebugILK fichtm ncovv=%d, kvar=TvarVV[ncovv]=V%d, ipos=TvarVVind[ncovv]=%d, Dummy[ipos]=%d, Typevar[ipos]=%d\n", ncovv,kvar,ipos,Dummy[ipos],Typevar[ipos]); *\/ */
4911: /* if(ipos!=iposold){ /\* Not a product or first of a product *\/ */
4912: /* /\* fprintf(ficresilk," V%d",TvarVV[ncovv]); *\/ */
4913: /* /\* printf(" DebugILK fichtm ipos=%d != iposold=%d\n", ipos, iposold); *\/ */
4914: /* if(Dummy[ipos]==0 && Typevar[ipos]==0){ /\* Only if dummy time varying: Dummy(0, 1=quant singor prod without age,2 dummy*age, 3quant*age) Typevar (0 single, 1=*age,2=Vn*vm) *\/ */
4915: /* for (k=1; k<= nlstate ; k++) { */
4916: /* fprintf(fichtm,"<br>- Probability p<sub>%dj</sub> by origin %d and destination j. Same dot size of all points but with a different color for transitions with dummy variable V%d=1 at beginning of transition (keeping former color for V%d=0): <a href=\"%s-p%dj.png\">%s-p%dj.png</a><br> \ */
4917: /* <img src=\"%s-p%dj-%d.png\">",k,k,kvar,kvar,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,subdirf2(optionfilefiname,"ILK_"),k,kvar); */
4918: /* } /\* End state *\/ */
4919: /* } /\* End only for dummies time varying (single?) *\/ */
4920: /* }else{ /\* Useless product *\/ */
4921: /* /\* printf("*"); *\/ */
4922: /* /\* fprintf(ficresilk,"*"); *\/ */
4923: /* } */
4924: /* iposold=ipos; */
4925: /* } /\* For each time varying covariate *\/ */
4926: /* }/\* End debugILK *\/ */
1.207 brouard 4927: fflush(fichtm);
1.343 brouard 4928: }/* End globpri */
1.126 brouard 4929: return;
4930: }
4931:
4932:
4933: /*********** Maximum Likelihood Estimation ***************/
4934:
4935: void mlikeli(FILE *ficres,double p[], int npar, int ncovmodel, int nlstate, double ftol, double (*func)(double []))
4936: {
1.319 brouard 4937: int i,j,k, jk, jkk=0, iter=0;
1.126 brouard 4938: double **xi;
4939: double fret;
4940: double fretone; /* Only one call to likelihood */
4941: /* char filerespow[FILENAMELENGTH];*/
1.354 ! brouard 4942:
! 4943: double * p1; /* Shifted parameters from 0 instead of 1 */
1.162 brouard 4944: #ifdef NLOPT
4945: int creturn;
4946: nlopt_opt opt;
4947: /* double lb[9] = { -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL, -HUGE_VAL }; /\* lower bounds *\/ */
4948: double *lb;
4949: double minf; /* the minimum objective value, upon return */
1.354 ! brouard 4950:
1.162 brouard 4951: myfunc_data dinst, *d = &dinst;
4952: #endif
4953:
4954:
1.126 brouard 4955: xi=matrix(1,npar,1,npar);
4956: for (i=1;i<=npar;i++)
4957: for (j=1;j<=npar;j++)
4958: xi[i][j]=(i==j ? 1.0 : 0.0);
4959: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.201 brouard 4960: strcpy(filerespow,"POW_");
1.126 brouard 4961: strcat(filerespow,fileres);
4962: if((ficrespow=fopen(filerespow,"w"))==NULL) {
4963: printf("Problem with resultfile: %s\n", filerespow);
4964: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
4965: }
4966: fprintf(ficrespow,"# Powell\n# iter -2*LL");
4967: for (i=1;i<=nlstate;i++)
4968: for(j=1;j<=nlstate+ndeath;j++)
4969: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
4970: fprintf(ficrespow,"\n");
1.162 brouard 4971: #ifdef POWELL
1.319 brouard 4972: #ifdef LINMINORIGINAL
4973: #else /* LINMINORIGINAL */
4974:
4975: flatdir=ivector(1,npar);
4976: for (j=1;j<=npar;j++) flatdir[j]=0;
4977: #endif /*LINMINORIGINAL */
4978:
4979: #ifdef FLATSUP
4980: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
4981: /* reorganizing p by suppressing flat directions */
4982: for(i=1, jk=1; i <=nlstate; i++){
4983: for(k=1; k <=(nlstate+ndeath); k++){
4984: if (k != i) {
4985: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
4986: if(flatdir[jk]==1){
4987: printf(" To be skipped %d%d flatdir[%d]=%d ",i,k,jk, flatdir[jk]);
4988: }
4989: for(j=1; j <=ncovmodel; j++){
4990: printf("%12.7f ",p[jk]);
4991: jk++;
4992: }
4993: printf("\n");
4994: }
4995: }
4996: }
4997: /* skipping */
4998: /* for(i=1, jk=1, jkk=1;(flatdir[jk]==0)&& (i <=nlstate); i++){ */
4999: for(i=1, jk=1, jkk=1;i <=nlstate; i++){
5000: for(k=1; k <=(nlstate+ndeath); k++){
5001: if (k != i) {
5002: printf("%d%d flatdir[%d]=%d",i,k,jk, flatdir[jk]);
5003: if(flatdir[jk]==1){
5004: printf(" To be skipped %d%d flatdir[%d]=%d jk=%d p[%d] ",i,k,jk, flatdir[jk],jk, jk);
5005: for(j=1; j <=ncovmodel; jk++,j++){
5006: printf(" p[%d]=%12.7f",jk, p[jk]);
5007: /*q[jjk]=p[jk];*/
5008: }
5009: }else{
5010: printf(" To be kept %d%d flatdir[%d]=%d jk=%d q[%d]=p[%d] ",i,k,jk, flatdir[jk],jk, jkk, jk);
5011: for(j=1; j <=ncovmodel; jk++,jkk++,j++){
5012: printf(" p[%d]=%12.7f=q[%d]",jk, p[jk],jkk);
5013: /*q[jjk]=p[jk];*/
5014: }
5015: }
5016: printf("\n");
5017: }
5018: fflush(stdout);
5019: }
5020: }
5021: powell(p,xi,npar,ftol,&iter,&fret,flatdir,func);
5022: #else /* FLATSUP */
1.126 brouard 5023: powell(p,xi,npar,ftol,&iter,&fret,func);
1.319 brouard 5024: #endif /* FLATSUP */
5025:
5026: #ifdef LINMINORIGINAL
5027: #else
5028: free_ivector(flatdir,1,npar);
5029: #endif /* LINMINORIGINAL*/
5030: #endif /* POWELL */
1.126 brouard 5031:
1.162 brouard 5032: #ifdef NLOPT
5033: #ifdef NEWUOA
5034: opt = nlopt_create(NLOPT_LN_NEWUOA,npar);
5035: #else
5036: opt = nlopt_create(NLOPT_LN_BOBYQA,npar);
5037: #endif
5038: lb=vector(0,npar-1);
5039: for (i=0;i<npar;i++) lb[i]= -HUGE_VAL;
5040: nlopt_set_lower_bounds(opt, lb);
5041: nlopt_set_initial_step1(opt, 0.1);
5042:
5043: p1= (p+1); /* p *(p+1)@8 and p *(p1)@8 are equal p1[0]=p[1] */
5044: d->function = func;
5045: printf(" Func %.12lf \n",myfunc(npar,p1,NULL,d));
5046: nlopt_set_min_objective(opt, myfunc, d);
5047: nlopt_set_xtol_rel(opt, ftol);
5048: if ((creturn=nlopt_optimize(opt, p1, &minf)) < 0) {
5049: printf("nlopt failed! %d\n",creturn);
5050: }
5051: else {
5052: printf("found minimum after %d evaluations (NLOPT=%d)\n", countcallfunc ,NLOPT);
5053: printf("found minimum at f(%g,%g) = %0.10g\n", p[0], p[1], minf);
5054: iter=1; /* not equal */
5055: }
5056: nlopt_destroy(opt);
5057: #endif
1.319 brouard 5058: #ifdef FLATSUP
5059: /* npared = npar -flatd/ncovmodel; */
5060: /* xired= matrix(1,npared,1,npared); */
5061: /* paramred= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */
5062: /* powell(pred,xired,npared,ftol,&iter,&fret,flatdir,func); */
5063: /* free_matrix(xire,1,npared,1,npared); */
5064: #else /* FLATSUP */
5065: #endif /* FLATSUP */
1.126 brouard 5066: free_matrix(xi,1,npar,1,npar);
5067: fclose(ficrespow);
1.203 brouard 5068: printf("\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
5069: fprintf(ficlog,"\n#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.180 brouard 5070: fprintf(ficres,"#Number of iterations & function calls = %d & %d, -2 Log likelihood = %.12f\n",iter, countcallfunc,func(p));
1.126 brouard 5071:
5072: }
5073:
5074: /**** Computes Hessian and covariance matrix ***/
1.203 brouard 5075: void hesscov(double **matcov, double **hess, double p[], int npar, double delti[], double ftolhess, double (*func)(double []))
1.126 brouard 5076: {
5077: double **a,**y,*x,pd;
1.203 brouard 5078: /* double **hess; */
1.164 brouard 5079: int i, j;
1.126 brouard 5080: int *indx;
5081:
5082: double hessii(double p[], double delta, int theta, double delti[],double (*func)(double []),int npar);
1.203 brouard 5083: double hessij(double p[], double **hess, double delti[], int i, int j,double (*func)(double []),int npar);
1.126 brouard 5084: void lubksb(double **a, int npar, int *indx, double b[]) ;
5085: void ludcmp(double **a, int npar, int *indx, double *d) ;
5086: double gompertz(double p[]);
1.203 brouard 5087: /* hess=matrix(1,npar,1,npar); */
1.126 brouard 5088:
5089: printf("\nCalculation of the hessian matrix. Wait...\n");
5090: fprintf(ficlog,"\nCalculation of the hessian matrix. Wait...\n");
5091: for (i=1;i<=npar;i++){
1.203 brouard 5092: printf("%d-",i);fflush(stdout);
5093: fprintf(ficlog,"%d-",i);fflush(ficlog);
1.126 brouard 5094:
5095: hess[i][i]=hessii(p,ftolhess,i,delti,func,npar);
5096:
5097: /* printf(" %f ",p[i]);
5098: printf(" %lf %lf %lf",hess[i][i],ftolhess,delti[i]);*/
5099: }
5100:
5101: for (i=1;i<=npar;i++) {
5102: for (j=1;j<=npar;j++) {
5103: if (j>i) {
1.203 brouard 5104: printf(".%d-%d",i,j);fflush(stdout);
5105: fprintf(ficlog,".%d-%d",i,j);fflush(ficlog);
5106: hess[i][j]=hessij(p,hess, delti,i,j,func,npar);
1.126 brouard 5107:
5108: hess[j][i]=hess[i][j];
5109: /*printf(" %lf ",hess[i][j]);*/
5110: }
5111: }
5112: }
5113: printf("\n");
5114: fprintf(ficlog,"\n");
5115:
5116: printf("\nInverting the hessian to get the covariance matrix. Wait...\n");
5117: fprintf(ficlog,"\nInverting the hessian to get the covariance matrix. Wait...\n");
5118:
5119: a=matrix(1,npar,1,npar);
5120: y=matrix(1,npar,1,npar);
5121: x=vector(1,npar);
5122: indx=ivector(1,npar);
5123: for (i=1;i<=npar;i++)
5124: for (j=1;j<=npar;j++) a[i][j]=hess[i][j];
5125: ludcmp(a,npar,indx,&pd);
5126:
5127: for (j=1;j<=npar;j++) {
5128: for (i=1;i<=npar;i++) x[i]=0;
5129: x[j]=1;
5130: lubksb(a,npar,indx,x);
5131: for (i=1;i<=npar;i++){
5132: matcov[i][j]=x[i];
5133: }
5134: }
5135:
5136: printf("\n#Hessian matrix#\n");
5137: fprintf(ficlog,"\n#Hessian matrix#\n");
5138: for (i=1;i<=npar;i++) {
5139: for (j=1;j<=npar;j++) {
1.203 brouard 5140: printf("%.6e ",hess[i][j]);
5141: fprintf(ficlog,"%.6e ",hess[i][j]);
1.126 brouard 5142: }
5143: printf("\n");
5144: fprintf(ficlog,"\n");
5145: }
5146:
1.203 brouard 5147: /* printf("\n#Covariance matrix#\n"); */
5148: /* fprintf(ficlog,"\n#Covariance matrix#\n"); */
5149: /* for (i=1;i<=npar;i++) { */
5150: /* for (j=1;j<=npar;j++) { */
5151: /* printf("%.6e ",matcov[i][j]); */
5152: /* fprintf(ficlog,"%.6e ",matcov[i][j]); */
5153: /* } */
5154: /* printf("\n"); */
5155: /* fprintf(ficlog,"\n"); */
5156: /* } */
5157:
1.126 brouard 5158: /* Recompute Inverse */
1.203 brouard 5159: /* for (i=1;i<=npar;i++) */
5160: /* for (j=1;j<=npar;j++) a[i][j]=matcov[i][j]; */
5161: /* ludcmp(a,npar,indx,&pd); */
5162:
5163: /* printf("\n#Hessian matrix recomputed#\n"); */
5164:
5165: /* for (j=1;j<=npar;j++) { */
5166: /* for (i=1;i<=npar;i++) x[i]=0; */
5167: /* x[j]=1; */
5168: /* lubksb(a,npar,indx,x); */
5169: /* for (i=1;i<=npar;i++){ */
5170: /* y[i][j]=x[i]; */
5171: /* printf("%.3e ",y[i][j]); */
5172: /* fprintf(ficlog,"%.3e ",y[i][j]); */
5173: /* } */
5174: /* printf("\n"); */
5175: /* fprintf(ficlog,"\n"); */
5176: /* } */
5177:
5178: /* Verifying the inverse matrix */
5179: #ifdef DEBUGHESS
5180: y=matprod2(y,hess,1,npar,1,npar,1,npar,matcov);
1.126 brouard 5181:
1.203 brouard 5182: printf("\n#Verification: multiplying the matrix of covariance by the Hessian matrix, should be unity:#\n");
5183: fprintf(ficlog,"\n#Verification: multiplying the matrix of covariance by the Hessian matrix. Should be unity:#\n");
1.126 brouard 5184:
5185: for (j=1;j<=npar;j++) {
5186: for (i=1;i<=npar;i++){
1.203 brouard 5187: printf("%.2f ",y[i][j]);
5188: fprintf(ficlog,"%.2f ",y[i][j]);
1.126 brouard 5189: }
5190: printf("\n");
5191: fprintf(ficlog,"\n");
5192: }
1.203 brouard 5193: #endif
1.126 brouard 5194:
5195: free_matrix(a,1,npar,1,npar);
5196: free_matrix(y,1,npar,1,npar);
5197: free_vector(x,1,npar);
5198: free_ivector(indx,1,npar);
1.203 brouard 5199: /* free_matrix(hess,1,npar,1,npar); */
1.126 brouard 5200:
5201:
5202: }
5203:
5204: /*************** hessian matrix ****************/
5205: double hessii(double x[], double delta, int theta, double delti[], double (*func)(double []), int npar)
1.203 brouard 5206: { /* Around values of x, computes the function func and returns the scales delti and hessian */
1.126 brouard 5207: int i;
5208: int l=1, lmax=20;
1.203 brouard 5209: double k1,k2, res, fx;
1.132 brouard 5210: double p2[MAXPARM+1]; /* identical to x */
1.126 brouard 5211: double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4;
5212: int k=0,kmax=10;
5213: double l1;
5214:
5215: fx=func(x);
5216: for (i=1;i<=npar;i++) p2[i]=x[i];
1.145 brouard 5217: for(l=0 ; l <=lmax; l++){ /* Enlarging the zone around the Maximum */
1.126 brouard 5218: l1=pow(10,l);
5219: delts=delt;
5220: for(k=1 ; k <kmax; k=k+1){
5221: delt = delta*(l1*k);
5222: p2[theta]=x[theta] +delt;
1.145 brouard 5223: k1=func(p2)-fx; /* Might be negative if too close to the theoretical maximum */
1.126 brouard 5224: p2[theta]=x[theta]-delt;
5225: k2=func(p2)-fx;
5226: /*res= (k1-2.0*fx+k2)/delt/delt; */
1.203 brouard 5227: res= (k1+k2)/delt/delt/2.; /* Divided by 2 because L and not 2*L */
1.126 brouard 5228:
1.203 brouard 5229: #ifdef DEBUGHESSII
1.126 brouard 5230: printf("%d %d k1=%.12e k2=%.12e xk1=%.12e xk2=%.12e delt=%.12e res=%.12e l=%d k=%d,fx=%.12e\n",theta,theta,k1,k2,x[theta]+delt,x[theta]-delt,delt,res, l, k,fx);
5231: fprintf(ficlog,"%d %d k1=%.12e k2=%.12e xk1=%.12e xk2=%.12e delt=%.12e res=%.12e l=%d k=%d,fx=%.12e\n",theta,theta,k1,k2,x[theta]+delt,x[theta]-delt,delt,res, l, k,fx);
5232: #endif
5233: /*if(fabs(k1-2.0*fx+k2) <1.e-13){ */
5234: if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)){
5235: k=kmax;
5236: }
5237: else if((k1 >khi/nkhif) || (k2 >khi/nkhif)){ /* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. */
1.164 brouard 5238: k=kmax; l=lmax*10;
1.126 brouard 5239: }
5240: else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){
5241: delts=delt;
5242: }
1.203 brouard 5243: } /* End loop k */
1.126 brouard 5244: }
5245: delti[theta]=delts;
5246: return res;
5247:
5248: }
5249:
1.203 brouard 5250: double hessij( double x[], double **hess, double delti[], int thetai,int thetaj,double (*func)(double []),int npar)
1.126 brouard 5251: {
5252: int i;
1.164 brouard 5253: int l=1, lmax=20;
1.126 brouard 5254: double k1,k2,k3,k4,res,fx;
1.132 brouard 5255: double p2[MAXPARM+1];
1.203 brouard 5256: int k, kmax=1;
5257: double v1, v2, cv12, lc1, lc2;
1.208 brouard 5258:
5259: int firstime=0;
1.203 brouard 5260:
1.126 brouard 5261: fx=func(x);
1.203 brouard 5262: for (k=1; k<=kmax; k=k+10) {
1.126 brouard 5263: for (i=1;i<=npar;i++) p2[i]=x[i];
1.203 brouard 5264: p2[thetai]=x[thetai]+delti[thetai]*k;
5265: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5266: k1=func(p2)-fx;
5267:
1.203 brouard 5268: p2[thetai]=x[thetai]+delti[thetai]*k;
5269: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5270: k2=func(p2)-fx;
5271:
1.203 brouard 5272: p2[thetai]=x[thetai]-delti[thetai]*k;
5273: p2[thetaj]=x[thetaj]+delti[thetaj]*k;
1.126 brouard 5274: k3=func(p2)-fx;
5275:
1.203 brouard 5276: p2[thetai]=x[thetai]-delti[thetai]*k;
5277: p2[thetaj]=x[thetaj]-delti[thetaj]*k;
1.126 brouard 5278: k4=func(p2)-fx;
1.203 brouard 5279: res=(k1-k2-k3+k4)/4.0/delti[thetai]/k/delti[thetaj]/k/2.; /* Because of L not 2*L */
5280: if(k1*k2*k3*k4 <0.){
1.208 brouard 5281: firstime=1;
1.203 brouard 5282: kmax=kmax+10;
1.208 brouard 5283: }
5284: if(kmax >=10 || firstime ==1){
1.354 ! brouard 5285: /* What are the thetai and thetaj? thetai/ncovmodel thetai=(thetai-thetai%ncovmodel)/ncovmodel +thetai%ncovmodel=(line,pos) */
1.246 brouard 5286: printf("Warning: directions %d-%d, you are not estimating the Hessian at the exact maximum likelihood; you could increase ftol=%.2e\n",thetai,thetaj, ftol);
5287: fprintf(ficlog,"Warning: directions %d-%d, you are not estimating the Hessian at the exact maximum likelihood; you could increase ftol=%.2e\n",thetai,thetaj, ftol);
1.203 brouard 5288: printf("%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti*k=%.12e deltj*k=%.12e, xi-de*k=%.12e xj-de*k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4);
5289: fprintf(ficlog,"%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti*k=%.12e deltj*k=%.12e, xi-de*k=%.12e xj-de*k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4);
5290: }
5291: #ifdef DEBUGHESSIJ
5292: v1=hess[thetai][thetai];
5293: v2=hess[thetaj][thetaj];
5294: cv12=res;
5295: /* Computing eigen value of Hessian matrix */
5296: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5297: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
5298: if ((lc2 <0) || (lc1 <0) ){
5299: printf("Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5300: fprintf(ficlog, "Warning: sub Hessian matrix '%d%d' does not have positive eigen values \n",thetai,thetaj);
5301: printf("%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4);
5302: fprintf(ficlog,"%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4);
5303: }
1.126 brouard 5304: #endif
5305: }
5306: return res;
5307: }
5308:
1.203 brouard 5309: /* Not done yet: Was supposed to fix if not exactly at the maximum */
5310: /* double hessij( double x[], double delti[], int thetai,int thetaj,double (*func)(double []),int npar) */
5311: /* { */
5312: /* int i; */
5313: /* int l=1, lmax=20; */
5314: /* double k1,k2,k3,k4,res,fx; */
5315: /* double p2[MAXPARM+1]; */
5316: /* double delt=0.0001, delts, nkhi=10.,nkhif=1., khi=1.e-4; */
5317: /* int k=0,kmax=10; */
5318: /* double l1; */
5319:
5320: /* fx=func(x); */
5321: /* for(l=0 ; l <=lmax; l++){ /\* Enlarging the zone around the Maximum *\/ */
5322: /* l1=pow(10,l); */
5323: /* delts=delt; */
5324: /* for(k=1 ; k <kmax; k=k+1){ */
5325: /* delt = delti*(l1*k); */
5326: /* for (i=1;i<=npar;i++) p2[i]=x[i]; */
5327: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5328: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5329: /* k1=func(p2)-fx; */
5330:
5331: /* p2[thetai]=x[thetai]+delti[thetai]/k; */
5332: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5333: /* k2=func(p2)-fx; */
5334:
5335: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5336: /* p2[thetaj]=x[thetaj]+delti[thetaj]/k; */
5337: /* k3=func(p2)-fx; */
5338:
5339: /* p2[thetai]=x[thetai]-delti[thetai]/k; */
5340: /* p2[thetaj]=x[thetaj]-delti[thetaj]/k; */
5341: /* k4=func(p2)-fx; */
5342: /* res=(k1-k2-k3+k4)/4.0/delti[thetai]*k/delti[thetaj]*k/2.; /\* Because of L not 2*L *\/ */
5343: /* #ifdef DEBUGHESSIJ */
5344: /* printf("%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4); */
5345: /* fprintf(ficlog,"%d %d k=%d, k1=%.12e k2=%.12e k3=%.12e k4=%.12e delti/k=%.12e deltj/k=%.12e, xi-de/k=%.12e xj-de/k=%.12e res=%.12e k1234=%.12e,k1-2=%.12e,k3-4=%.12e\n",thetai,thetaj,k,k1,k2,k3,k4,delti[thetai]/k,delti[thetaj]/k,x[thetai]-delti[thetai]/k,x[thetaj]-delti[thetaj]/k, res,k1-k2-k3+k4,k1-k2,k3-k4); */
5346: /* #endif */
5347: /* if((k1 <khi/nkhi/2.) || (k2 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)|| (k4 <khi/nkhi/2.)){ */
5348: /* k=kmax; */
5349: /* } */
5350: /* else if((k1 >khi/nkhif) || (k2 >khi/nkhif) || (k4 >khi/nkhif) || (k4 >khi/nkhif)){ /\* Keeps lastvalue before 3.84/2 KHI2 5% 1d.f. *\/ */
5351: /* k=kmax; l=lmax*10; */
5352: /* } */
5353: /* else if((k1 >khi/nkhi) || (k2 >khi/nkhi)){ */
5354: /* delts=delt; */
5355: /* } */
5356: /* } /\* End loop k *\/ */
5357: /* } */
5358: /* delti[theta]=delts; */
5359: /* return res; */
5360: /* } */
5361:
5362:
1.126 brouard 5363: /************** Inverse of matrix **************/
5364: void ludcmp(double **a, int n, int *indx, double *d)
5365: {
5366: int i,imax,j,k;
5367: double big,dum,sum,temp;
5368: double *vv;
5369:
5370: vv=vector(1,n);
5371: *d=1.0;
5372: for (i=1;i<=n;i++) {
5373: big=0.0;
5374: for (j=1;j<=n;j++)
5375: if ((temp=fabs(a[i][j])) > big) big=temp;
1.256 brouard 5376: if (big == 0.0){
5377: printf(" Singular Hessian matrix at row %d:\n",i);
5378: for (j=1;j<=n;j++) {
5379: printf(" a[%d][%d]=%f,",i,j,a[i][j]);
5380: fprintf(ficlog," a[%d][%d]=%f,",i,j,a[i][j]);
5381: }
5382: fflush(ficlog);
5383: fclose(ficlog);
5384: nrerror("Singular matrix in routine ludcmp");
5385: }
1.126 brouard 5386: vv[i]=1.0/big;
5387: }
5388: for (j=1;j<=n;j++) {
5389: for (i=1;i<j;i++) {
5390: sum=a[i][j];
5391: for (k=1;k<i;k++) sum -= a[i][k]*a[k][j];
5392: a[i][j]=sum;
5393: }
5394: big=0.0;
5395: for (i=j;i<=n;i++) {
5396: sum=a[i][j];
5397: for (k=1;k<j;k++)
5398: sum -= a[i][k]*a[k][j];
5399: a[i][j]=sum;
5400: if ( (dum=vv[i]*fabs(sum)) >= big) {
5401: big=dum;
5402: imax=i;
5403: }
5404: }
5405: if (j != imax) {
5406: for (k=1;k<=n;k++) {
5407: dum=a[imax][k];
5408: a[imax][k]=a[j][k];
5409: a[j][k]=dum;
5410: }
5411: *d = -(*d);
5412: vv[imax]=vv[j];
5413: }
5414: indx[j]=imax;
5415: if (a[j][j] == 0.0) a[j][j]=TINY;
5416: if (j != n) {
5417: dum=1.0/(a[j][j]);
5418: for (i=j+1;i<=n;i++) a[i][j] *= dum;
5419: }
5420: }
5421: free_vector(vv,1,n); /* Doesn't work */
5422: ;
5423: }
5424:
5425: void lubksb(double **a, int n, int *indx, double b[])
5426: {
5427: int i,ii=0,ip,j;
5428: double sum;
5429:
5430: for (i=1;i<=n;i++) {
5431: ip=indx[i];
5432: sum=b[ip];
5433: b[ip]=b[i];
5434: if (ii)
5435: for (j=ii;j<=i-1;j++) sum -= a[i][j]*b[j];
5436: else if (sum) ii=i;
5437: b[i]=sum;
5438: }
5439: for (i=n;i>=1;i--) {
5440: sum=b[i];
5441: for (j=i+1;j<=n;j++) sum -= a[i][j]*b[j];
5442: b[i]=sum/a[i][i];
5443: }
5444: }
5445:
5446: void pstamp(FILE *fichier)
5447: {
1.196 brouard 5448: fprintf(fichier,"# %s.%s\n#IMaCh version %s, %s\n#%s\n# %s", optionfilefiname,optionfilext,version,copyright, fullversion, strstart);
1.126 brouard 5449: }
5450:
1.297 brouard 5451: void date2dmy(double date,double *day, double *month, double *year){
5452: double yp=0., yp1=0., yp2=0.;
5453:
5454: yp1=modf(date,&yp);/* extracts integral of date in yp and
5455: fractional in yp1 */
5456: *year=yp;
5457: yp2=modf((yp1*12),&yp);
5458: *month=yp;
5459: yp1=modf((yp2*30.5),&yp);
5460: *day=yp;
5461: if(*day==0) *day=1;
5462: if(*month==0) *month=1;
5463: }
5464:
1.253 brouard 5465:
5466:
1.126 brouard 5467: /************ Frequencies ********************/
1.251 brouard 5468: void freqsummary(char fileres[], double p[], double pstart[], int iagemin, int iagemax, int **s, double **agev, int nlstate, int imx, \
1.226 brouard 5469: int *Tvaraff, int *invalidvarcomb, int **nbcode, int *ncodemax,double **mint,double **anint, char strstart[], \
5470: int firstpass, int lastpass, int stepm, int weightopt, char model[])
1.250 brouard 5471: { /* Some frequencies as well as proposing some starting values */
1.332 brouard 5472: /* Frequencies of any combination of dummy covariate used in the model equation */
1.265 brouard 5473: int i, m, jk, j1, bool, z1,j, nj, nl, k, iv, jj=0, s1=1, s2=1;
1.226 brouard 5474: int iind=0, iage=0;
5475: int mi; /* Effective wave */
5476: int first;
5477: double ***freq; /* Frequencies */
1.268 brouard 5478: double *x, *y, a=0.,b=0.,r=1., sa=0., sb=0.; /* for regression, y=b+m*x and r is the correlation coefficient */
5479: int no=0, linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb);
1.284 brouard 5480: double *meanq, *stdq, *idq;
1.226 brouard 5481: double **meanqt;
5482: double *pp, **prop, *posprop, *pospropt;
5483: double pos=0., posproptt=0., pospropta=0., k2, dateintsum=0,k2cpt=0;
5484: char fileresp[FILENAMELENGTH], fileresphtm[FILENAMELENGTH], fileresphtmfr[FILENAMELENGTH];
5485: double agebegin, ageend;
5486:
5487: pp=vector(1,nlstate);
1.251 brouard 5488: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5489: posprop=vector(1,nlstate); /* Counting the number of transition starting from a live state per age */
5490: pospropt=vector(1,nlstate); /* Counting the number of transition starting from a live state */
5491: /* prop=matrix(1,nlstate,iagemin,iagemax+3); */
5492: meanq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.284 brouard 5493: stdq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.283 brouard 5494: idq=vector(1,nqfveff); /* Number of Quantitative Fixed Variables Effective */
1.226 brouard 5495: meanqt=matrix(1,lastpass,1,nqtveff);
5496: strcpy(fileresp,"P_");
5497: strcat(fileresp,fileresu);
5498: /*strcat(fileresphtm,fileresu);*/
5499: if((ficresp=fopen(fileresp,"w"))==NULL) {
5500: printf("Problem with prevalence resultfile: %s\n", fileresp);
5501: fprintf(ficlog,"Problem with prevalence resultfile: %s\n", fileresp);
5502: exit(0);
5503: }
1.240 brouard 5504:
1.226 brouard 5505: strcpy(fileresphtm,subdirfext(optionfilefiname,"PHTM_",".htm"));
5506: if((ficresphtm=fopen(fileresphtm,"w"))==NULL) {
5507: printf("Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5508: fprintf(ficlog,"Problem with prevalence HTM resultfile '%s' with errno='%s'\n",fileresphtm,strerror(errno));
5509: fflush(ficlog);
5510: exit(70);
5511: }
5512: else{
5513: fprintf(ficresphtm,"<html><head>\n<title>IMaCh PHTM_ %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.240 brouard 5514: <hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5515: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5516: fileresphtm,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5517: }
1.319 brouard 5518: fprintf(ficresphtm,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Frequencies (weight=%d) and prevalence by age at begin of transition and dummy covariate value at beginning of transition</h4>\n",fileresphtm, fileresphtm, weightopt);
1.240 brouard 5519:
1.226 brouard 5520: strcpy(fileresphtmfr,subdirfext(optionfilefiname,"PHTMFR_",".htm"));
5521: if((ficresphtmfr=fopen(fileresphtmfr,"w"))==NULL) {
5522: printf("Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5523: fprintf(ficlog,"Problem with frequency table HTM resultfile '%s' with errno='%s'\n",fileresphtmfr,strerror(errno));
5524: fflush(ficlog);
5525: exit(70);
1.240 brouard 5526: } else{
1.226 brouard 5527: fprintf(ficresphtmfr,"<html><head>\n<title>IMaCh PHTM_Frequency table %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
1.319 brouard 5528: ,<hr size=\"2\" color=\"#EC5E5E\"> \n \
1.214 brouard 5529: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.226 brouard 5530: fileresphtmfr,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
5531: }
1.319 brouard 5532: fprintf(ficresphtmfr,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>(weight=%d) frequencies of all effective transitions of the model, by age at begin of transition, and covariate value at the begin of transition (if the covariate is a varying covariate) </h4>Unknown status is -1<br/>\n",fileresphtmfr, fileresphtmfr,weightopt);
1.240 brouard 5533:
1.253 brouard 5534: y= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
5535: x= vector(iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.251 brouard 5536: freq= ma3x(-5,nlstate+ndeath,-5,nlstate+ndeath,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.226 brouard 5537: j1=0;
1.126 brouard 5538:
1.227 brouard 5539: /* j=ncoveff; /\* Only fixed dummy covariates *\/ */
1.335 brouard 5540: j=cptcoveff; /* Only simple dummy covariates used in the model */
1.330 brouard 5541: /* j=cptcovn; /\* Only dummy covariates of the model *\/ */
1.226 brouard 5542: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.240 brouard 5543:
5544:
1.226 brouard 5545: /* Detects if a combination j1 is empty: for a multinomial variable like 3 education levels:
5546: reference=low_education V1=0,V2=0
5547: med_educ V1=1 V2=0,
5548: high_educ V1=0 V2=1
1.330 brouard 5549: Then V1=1 and V2=1 is a noisy combination that we want to exclude for the list 2**cptcovn
1.226 brouard 5550: */
1.249 brouard 5551: dateintsum=0;
5552: k2cpt=0;
5553:
1.253 brouard 5554: if(cptcoveff == 0 )
1.265 brouard 5555: nl=1; /* Constant and age model only */
1.253 brouard 5556: else
5557: nl=2;
1.265 brouard 5558:
5559: /* if a constant only model, one pass to compute frequency tables and to write it on ficresp */
5560: /* Loop on nj=1 or 2 if dummy covariates j!=0
1.335 brouard 5561: * Loop on j1(1 to 2**cptcoveff) covariate combination
1.265 brouard 5562: * freq[s1][s2][iage] =0.
5563: * Loop on iind
5564: * ++freq[s1][s2][iage] weighted
5565: * end iind
5566: * if covariate and j!0
5567: * headers Variable on one line
5568: * endif cov j!=0
5569: * header of frequency table by age
5570: * Loop on age
5571: * pp[s1]+=freq[s1][s2][iage] weighted
5572: * pos+=freq[s1][s2][iage] weighted
5573: * Loop on s1 initial state
5574: * fprintf(ficresp
5575: * end s1
5576: * end age
5577: * if j!=0 computes starting values
5578: * end compute starting values
5579: * end j1
5580: * end nl
5581: */
1.253 brouard 5582: for (nj = 1; nj <= nl; nj++){ /* nj= 1 constant model, nl number of loops. */
5583: if(nj==1)
5584: j=0; /* First pass for the constant */
1.265 brouard 5585: else{
1.335 brouard 5586: j=cptcoveff; /* Other passes for the covariate values number of simple covariates in the model V2+V1 =2 (simple dummy fixed or time varying) */
1.265 brouard 5587: }
1.251 brouard 5588: first=1;
1.332 brouard 5589: for (j1 = 1; j1 <= (int) pow(2,j); j1++){ /* Loop on all dummy covariates combination of the model, ie excluding quantitatives, V4=0, V3=0 for example, fixed or varying covariates */
1.251 brouard 5590: posproptt=0.;
1.330 brouard 5591: /*printf("cptcovn=%d Tvaraff=%d", cptcovn,Tvaraff[1]);
1.251 brouard 5592: scanf("%d", i);*/
5593: for (i=-5; i<=nlstate+ndeath; i++)
1.265 brouard 5594: for (s2=-5; s2<=nlstate+ndeath; s2++)
1.251 brouard 5595: for(m=iagemin; m <= iagemax+3; m++)
1.265 brouard 5596: freq[i][s2][m]=0;
1.251 brouard 5597:
5598: for (i=1; i<=nlstate; i++) {
1.240 brouard 5599: for(m=iagemin; m <= iagemax+3; m++)
1.251 brouard 5600: prop[i][m]=0;
5601: posprop[i]=0;
5602: pospropt[i]=0;
5603: }
1.283 brouard 5604: for (z1=1; z1<= nqfveff; z1++) { /* zeroing for each combination j1 as well as for the total */
1.284 brouard 5605: idq[z1]=0.;
5606: meanq[z1]=0.;
5607: stdq[z1]=0.;
1.283 brouard 5608: }
5609: /* for (z1=1; z1<= nqtveff; z1++) { */
1.251 brouard 5610: /* for(m=1;m<=lastpass;m++){ */
1.283 brouard 5611: /* meanqt[m][z1]=0.; */
5612: /* } */
5613: /* } */
1.251 brouard 5614: /* dateintsum=0; */
5615: /* k2cpt=0; */
5616:
1.265 brouard 5617: /* For that combination of covariates j1 (V4=1 V3=0 for example), we count and print the frequencies in one pass */
1.251 brouard 5618: for (iind=1; iind<=imx; iind++) { /* For each individual iind */
5619: bool=1;
5620: if(j !=0){
5621: if(anyvaryingduminmodel==0){ /* If All fixed covariates */
1.335 brouard 5622: if (cptcoveff >0) { /* Filter is here: Must be looked at for model=V1+V2+V3+V4 */
5623: for (z1=1; z1<=cptcoveff; z1++) { /* loops on covariates in the model */
1.251 brouard 5624: /* if(Tvaraff[z1] ==-20){ */
5625: /* /\* sumnew+=cotvar[mw[mi][iind]][z1][iind]; *\/ */
5626: /* }else if(Tvaraff[z1] ==-10){ */
5627: /* /\* sumnew+=coqvar[z1][iind]; *\/ */
1.330 brouard 5628: /* }else */ /* TODO TODO codtabm(j1,z1) or codtabm(j1,Tvaraff[z1]]z1)*/
1.335 brouard 5629: /* if( iind >=imx-3) printf("Searching error iind=%d Tvaraff[z1]=%d covar[Tvaraff[z1]][iind]=%.f TnsdVar[Tvaraff[z1]]=%d, cptcoveff=%d, cptcovs=%d \n",iind, Tvaraff[z1], covar[Tvaraff[z1]][iind],TnsdVar[Tvaraff[z1]],cptcoveff, cptcovs); */
5630: if(Tvaraff[z1]<1 || Tvaraff[z1]>=NCOVMAX)
1.338 brouard 5631: printf("Error Tvaraff[z1]=%d<1 or >=%d, cptcoveff=%d model=1+age+%s\n",Tvaraff[z1],NCOVMAX, cptcoveff, model);
1.332 brouard 5632: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]){ /* for combination j1 of covariates */
1.265 brouard 5633: /* Tests if the value of the covariate z1 for this individual iind responded to combination j1 (V4=1 V3=0) */
1.251 brouard 5634: bool=0; /* bool should be equal to 1 to be selected, one covariate value failed */
1.332 brouard 5635: /* printf("bool=%d i=%d, z1=%d, Tvaraff[%d]=%d, covar[Tvarff][%d]=%2f, codtabm(%d,%d)=%d, nbcode[Tvaraff][codtabm(%d,%d)=%d, j1=%d\n", */
5636: /* bool,i,z1, z1, Tvaraff[z1],i,covar[Tvaraff[z1]][i],j1,z1,codtabm(j1,z1),*/
5637: /* j1,z1,nbcode[Tvaraff[z1]][codtabm(j1,z1)],j1);*/
1.251 brouard 5638: /* For j1=7 in V1+V2+V3+V4 = 0 1 1 0 and codtabm(7,3)=1 and nbcde[3][?]=1*/
5639: } /* Onlyf fixed */
5640: } /* end z1 */
1.335 brouard 5641: } /* cptcoveff > 0 */
1.251 brouard 5642: } /* end any */
5643: }/* end j==0 */
1.265 brouard 5644: if (bool==1){ /* We selected an individual iind satisfying combination j1 (V4=1 V3=0) or all fixed covariates */
1.251 brouard 5645: /* for(m=firstpass; m<=lastpass; m++){ */
1.284 brouard 5646: for(mi=1; mi<wav[iind];mi++){ /* For each wave */
1.251 brouard 5647: m=mw[mi][iind];
5648: if(j!=0){
5649: if(anyvaryingduminmodel==1){ /* Some are varying covariates */
1.335 brouard 5650: for (z1=1; z1<=cptcoveff; z1++) {
1.251 brouard 5651: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 5652: /* iv= Tvar[Tmodelind[z1]]-ncovcol-nqv; /\* Good *\/ */
5653: iv= Tvar[Tmodelind[z1]]; /* Good *//* because cotvar starts now at first at ncovcol+nqv+ntv */
1.332 brouard 5654: if (cotvar[m][iv][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality. If covariate's
1.251 brouard 5655: value is -1, we don't select. It differs from the
5656: constant and age model which counts them. */
5657: bool=0; /* not selected */
5658: }else if( Fixed[Tmodelind[z1]]== 0) { /* fixed */
1.334 brouard 5659: /* i1=Tvaraff[z1]; */
5660: /* i2=TnsdVar[i1]; */
5661: /* i3=nbcode[i1][i2]; */
5662: /* i4=covar[i1][iind]; */
5663: /* if(i4 != i3){ */
5664: if (covar[Tvaraff[z1]][iind]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) { /* Bug valgrind */
1.251 brouard 5665: bool=0;
5666: }
5667: }
5668: }
5669: }/* Some are varying covariates, we tried to speed up if all fixed covariates in the model, avoiding waves loop */
5670: } /* end j==0 */
5671: /* bool =0 we keep that guy which corresponds to the combination of dummy values */
1.284 brouard 5672: if(bool==1){ /*Selected */
1.251 brouard 5673: /* dh[m][iind] or dh[mw[mi][iind]][iind] is the delay between two effective (mi) waves m=mw[mi][iind]
5674: and mw[mi+1][iind]. dh depends on stepm. */
5675: agebegin=agev[m][iind]; /* Age at beginning of wave before transition*/
5676: ageend=agev[m][iind]+(dh[m][iind])*stepm/YEARM; /* Age at end of wave and transition */
5677: if(m >=firstpass && m <=lastpass){
5678: k2=anint[m][iind]+(mint[m][iind]/12.);
5679: /*if ((k2>=dateprev1) && (k2<=dateprev2)) {*/
5680: if(agev[m][iind]==0) agev[m][iind]=iagemax+1; /* All ages equal to 0 are in iagemax+1 */
5681: if(agev[m][iind]==1) agev[m][iind]=iagemax+2; /* All ages equal to 1 are in iagemax+2 */
5682: if (s[m][iind]>0 && s[m][iind]<=nlstate) /* If status at wave m is known and a live state */
5683: prop[s[m][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
5684: if (m<lastpass) {
5685: /* if(s[m][iind]==4 && s[m+1][iind]==4) */
5686: /* printf(" num=%ld m=%d, iind=%d s1=%d s2=%d agev at m=%d\n", num[iind], m, iind,s[m][iind],s[m+1][iind], (int)agev[m][iind]); */
5687: if(s[m][iind]==-1)
5688: printf(" num=%ld m=%d, iind=%d s1=%d s2=%d agev at m=%d agebegin=%.2f ageend=%.2f, agemed=%d\n", num[iind], m, iind,s[m][iind],s[m+1][iind], (int)agev[m][iind],agebegin, ageend, (int)((agebegin+ageend)/2.));
5689: freq[s[m][iind]][s[m+1][iind]][(int)agev[m][iind]] += weight[iind]; /* At age of beginning of transition, where status is known */
1.311 brouard 5690: for (z1=1; z1<= nqfveff; z1++) { /* Quantitative variables, calculating mean on known values only */
5691: if(!isnan(covar[ncovcol+z1][iind])){
1.332 brouard 5692: idq[z1]=idq[z1]+weight[iind];
5693: meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /* Computes mean of quantitative with selected filter */
5694: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; *//*error*/
5695: stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]; /* *weight[iind];*/ /* Computes mean of quantitative with selected filter */
1.311 brouard 5696: }
1.284 brouard 5697: }
1.251 brouard 5698: /* if((int)agev[m][iind] == 55) */
5699: /* printf("j=%d, j1=%d Age %d, iind=%d, num=%09ld m=%d\n",j,j1,(int)agev[m][iind],iind, num[iind],m); */
5700: /* freq[s[m][iind]][s[m+1][iind]][(int)((agebegin+ageend)/2.)] += weight[iind]; */
5701: freq[s[m][iind]][s[m+1][iind]][iagemax+3] += weight[iind]; /* Total is in iagemax+3 *//* At age of beginning of transition, where status is known */
1.234 brouard 5702: }
1.251 brouard 5703: } /* end if between passes */
5704: if ((agev[m][iind]>1) && (agev[m][iind]< (iagemax+3)) && (anint[m][iind]!=9999) && (mint[m][iind]!=99) && (j==0)) {
5705: dateintsum=dateintsum+k2; /* on all covariates ?*/
5706: k2cpt++;
5707: /* printf("iind=%ld dateintmean = %lf dateintsum=%lf k2cpt=%lf k2=%lf\n",iind, dateintsum/k2cpt, dateintsum,k2cpt, k2); */
1.234 brouard 5708: }
1.251 brouard 5709: }else{
5710: bool=1;
5711: }/* end bool 2 */
5712: } /* end m */
1.284 brouard 5713: /* for (z1=1; z1<= nqfveff; z1++) { /\* Quantitative variables, calculating mean *\/ */
5714: /* idq[z1]=idq[z1]+weight[iind]; */
5715: /* meanq[z1]+=covar[ncovcol+z1][iind]*weight[iind]; /\* Computes mean of quantitative with selected filter *\/ */
5716: /* stdq[z1]+=covar[ncovcol+z1][iind]*covar[ncovcol+z1][iind]*weight[iind]*weight[iind]; /\* *weight[iind];*\/ /\* Computes mean of quantitative with selected filter *\/ */
5717: /* } */
1.251 brouard 5718: } /* end bool */
5719: } /* end iind = 1 to imx */
1.319 brouard 5720: /* prop[s][age] is fed for any initial and valid live state as well as
1.251 brouard 5721: freq[s1][s2][age] at single age of beginning the transition, for a combination j1 */
5722:
5723:
5724: /* fprintf(ficresp, "#Count between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2);*/
1.335 brouard 5725: if(cptcoveff==0 && nj==1) /* no covariate and first pass */
1.265 brouard 5726: pstamp(ficresp);
1.335 brouard 5727: if (cptcoveff>0 && j!=0){
1.265 brouard 5728: pstamp(ficresp);
1.251 brouard 5729: printf( "\n#********** Variable ");
5730: fprintf(ficresp, "\n#********** Variable ");
5731: fprintf(ficresphtm, "\n<br/><br/><h3>********** Variable ");
5732: fprintf(ficresphtmfr, "\n<br/><br/><h3>********** Variable ");
5733: fprintf(ficlog, "\n#********** Variable ");
1.340 brouard 5734: for (z1=1; z1<=cptcoveff; z1++){
1.251 brouard 5735: if(!FixedV[Tvaraff[z1]]){
1.330 brouard 5736: printf( "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5737: fprintf(ficresp, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5738: fprintf(ficresphtm, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5739: fprintf(ficresphtmfr, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5740: fprintf(ficlog, "V%d(fixed)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.250 brouard 5741: }else{
1.330 brouard 5742: printf( "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5743: fprintf(ficresp, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5744: fprintf(ficresphtm, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5745: fprintf(ficresphtmfr, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5746: fprintf(ficlog, "V%d(varying)=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.251 brouard 5747: }
5748: }
5749: printf( "**********\n#");
5750: fprintf(ficresp, "**********\n#");
5751: fprintf(ficresphtm, "**********</h3>\n");
5752: fprintf(ficresphtmfr, "**********</h3>\n");
5753: fprintf(ficlog, "**********\n");
5754: }
1.284 brouard 5755: /*
5756: Printing means of quantitative variables if any
5757: */
5758: for (z1=1; z1<= nqfveff; z1++) {
1.311 brouard 5759: fprintf(ficlog,"Mean of fixed quantitative variable V%d on %.3g (weighted) individuals sum=%f", ncovcol+z1, idq[z1], meanq[z1]);
1.312 brouard 5760: fprintf(ficlog,", mean=%.3g\n",meanq[z1]/idq[z1]);
1.284 brouard 5761: if(weightopt==1){
5762: printf(" Weighted mean and standard deviation of");
5763: fprintf(ficlog," Weighted mean and standard deviation of");
5764: fprintf(ficresphtmfr," Weighted mean and standard deviation of");
5765: }
1.311 brouard 5766: /* mu = \frac{w x}{\sum w}
5767: var = \frac{\sum w (x-mu)^2}{\sum w} = \frac{w x^2}{\sum w} - mu^2
5768: */
5769: printf(" fixed quantitative variable V%d on %.3g (weighted) representatives of the population : %8.5g (%8.5g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1]));
5770: fprintf(ficlog," fixed quantitative variable V%d on %.3g (weighted) representatives of the population : %8.5g (%8.5g)\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1]));
5771: fprintf(ficresphtmfr," fixed quantitative variable V%d on %.3g (weighted) representatives of the population : %8.5g (%8.5g)<p>\n", ncovcol+z1, idq[z1],meanq[z1]/idq[z1], sqrt(stdq[z1]/idq[z1]-meanq[z1]*meanq[z1]/idq[z1]/idq[z1]));
1.284 brouard 5772: }
5773: /* for (z1=1; z1<= nqtveff; z1++) { */
5774: /* for(m=1;m<=lastpass;m++){ */
5775: /* fprintf(ficresphtmfr,"V quantitative id %d, pass id=%d, mean=%f<p>\n", z1, m, meanqt[m][z1]); */
5776: /* } */
5777: /* } */
1.283 brouard 5778:
1.251 brouard 5779: fprintf(ficresphtm,"<table style=\"text-align:center; border: 1px solid\">");
1.335 brouard 5780: if((cptcoveff==0 && nj==1)|| nj==2 ) /* no covariate and first pass */
1.265 brouard 5781: fprintf(ficresp, " Age");
1.335 brouard 5782: if(nj==2) for (z1=1; z1<=cptcoveff; z1++) {
5783: printf(" V%d=%d, z1=%d, Tvaraff[z1]=%d, j1=%d, TnsdVar[Tvaraff[%d]]=%d |",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])], z1, Tvaraff[z1], j1,z1,TnsdVar[Tvaraff[z1]]);
5784: fprintf(ficresp, " V%d=%d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
5785: }
1.251 brouard 5786: for(i=1; i<=nlstate;i++) {
1.335 brouard 5787: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," Prev(%d) N(%d) N ",i,i);
1.251 brouard 5788: fprintf(ficresphtm, "<th>Age</th><th>Prev(%d)</th><th>N(%d)</th><th>N</th>",i,i);
5789: }
1.335 brouard 5790: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp, "\n");
1.251 brouard 5791: fprintf(ficresphtm, "\n");
5792:
5793: /* Header of frequency table by age */
5794: fprintf(ficresphtmfr,"<table style=\"text-align:center; border: 1px solid\">");
5795: fprintf(ficresphtmfr,"<th>Age</th> ");
1.265 brouard 5796: for(s2=-1; s2 <=nlstate+ndeath; s2++){
1.251 brouard 5797: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5798: if(s2!=0 && m!=0)
5799: fprintf(ficresphtmfr,"<th>%d%d</th> ",s2,m);
1.240 brouard 5800: }
1.226 brouard 5801: }
1.251 brouard 5802: fprintf(ficresphtmfr, "\n");
5803:
5804: /* For each age */
5805: for(iage=iagemin; iage <= iagemax+3; iage++){
5806: fprintf(ficresphtm,"<tr>");
5807: if(iage==iagemax+1){
5808: fprintf(ficlog,"1");
5809: fprintf(ficresphtmfr,"<tr><th>0</th> ");
5810: }else if(iage==iagemax+2){
5811: fprintf(ficlog,"0");
5812: fprintf(ficresphtmfr,"<tr><th>Unknown</th> ");
5813: }else if(iage==iagemax+3){
5814: fprintf(ficlog,"Total");
5815: fprintf(ficresphtmfr,"<tr><th>Total</th> ");
5816: }else{
1.240 brouard 5817: if(first==1){
1.251 brouard 5818: first=0;
5819: printf("See log file for details...\n");
5820: }
5821: fprintf(ficresphtmfr,"<tr><th>%d</th> ",iage);
5822: fprintf(ficlog,"Age %d", iage);
5823: }
1.265 brouard 5824: for(s1=1; s1 <=nlstate ; s1++){
5825: for(m=-1, pp[s1]=0; m <=nlstate+ndeath ; m++)
5826: pp[s1] += freq[s1][m][iage];
1.251 brouard 5827: }
1.265 brouard 5828: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5829: for(m=-1, pos=0; m <=0 ; m++)
1.265 brouard 5830: pos += freq[s1][m][iage];
5831: if(pp[s1]>=1.e-10){
1.251 brouard 5832: if(first==1){
1.265 brouard 5833: printf(" %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5834: }
1.265 brouard 5835: fprintf(ficlog," %d.=%.0f loss[%d]=%.1f%%",s1,pp[s1],s1,100*pos/pp[s1]);
1.251 brouard 5836: }else{
5837: if(first==1)
1.265 brouard 5838: printf(" %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
5839: fprintf(ficlog," %d.=%.0f loss[%d]=NaNQ%%",s1,pp[s1],s1);
1.240 brouard 5840: }
5841: }
5842:
1.265 brouard 5843: for(s1=1; s1 <=nlstate ; s1++){
5844: /* posprop[s1]=0; */
5845: for(m=0, pp[s1]=0; m <=nlstate+ndeath; m++)/* Summing on all ages */
5846: pp[s1] += freq[s1][m][iage];
5847: } /* pp[s1] is the total number of transitions starting from state s1 and any ending status until this age */
5848:
5849: for(s1=1,pos=0, pospropta=0.; s1 <=nlstate ; s1++){
5850: pos += pp[s1]; /* pos is the total number of transitions until this age */
5851: posprop[s1] += prop[s1][iage]; /* prop is the number of transitions from a live state
5852: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5853: pospropta += prop[s1][iage]; /* prop is the number of transitions from a live state
5854: from s1 at age iage prop[s[m][iind]][(int)agev[m][iind]] += weight[iind] */
5855: }
5856:
5857: /* Writing ficresp */
1.335 brouard 5858: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5859: if( iage <= iagemax){
5860: fprintf(ficresp," %d",iage);
5861: }
5862: }else if( nj==2){
5863: if( iage <= iagemax){
5864: fprintf(ficresp," %d",iage);
1.335 brouard 5865: for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresp, " %d %d",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]);
1.265 brouard 5866: }
1.240 brouard 5867: }
1.265 brouard 5868: for(s1=1; s1 <=nlstate ; s1++){
1.240 brouard 5869: if(pos>=1.e-5){
1.251 brouard 5870: if(first==1)
1.265 brouard 5871: printf(" %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
5872: fprintf(ficlog," %d.=%.0f prev[%d]=%.1f%%",s1,pp[s1],s1,100*pp[s1]/pos);
1.251 brouard 5873: }else{
5874: if(first==1)
1.265 brouard 5875: printf(" %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
5876: fprintf(ficlog," %d.=%.0f prev[%d]=NaNQ%%",s1,pp[s1],s1);
1.251 brouard 5877: }
5878: if( iage <= iagemax){
5879: if(pos>=1.e-5){
1.335 brouard 5880: if(cptcoveff==0 && nj==1){ /* no covariate and first pass */
1.265 brouard 5881: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5882: }else if( nj==2){
5883: fprintf(ficresp," %.5f %.0f %.0f",prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5884: }
5885: fprintf(ficresphtm,"<th>%d</th><td>%.5f</td><td>%.0f</td><td>%.0f</td>",iage,prop[s1][iage]/pospropta, prop[s1][iage],pospropta);
5886: /*probs[iage][s1][j1]= pp[s1]/pos;*/
5887: /*printf("\niage=%d s1=%d j1=%d %.5f %.0f %.0f %f",iage,s1,j1,pp[s1]/pos, pp[s1],pos,probs[iage][s1][j1]);*/
5888: } else{
1.335 brouard 5889: if((cptcoveff==0 && nj==1)|| nj==2 ) fprintf(ficresp," NaNq %.0f %.0f",prop[s1][iage],pospropta);
1.265 brouard 5890: fprintf(ficresphtm,"<th>%d</th><td>NaNq</td><td>%.0f</td><td>%.0f</td>",iage, prop[s1][iage],pospropta);
1.251 brouard 5891: }
1.240 brouard 5892: }
1.265 brouard 5893: pospropt[s1] +=posprop[s1];
5894: } /* end loop s1 */
1.251 brouard 5895: /* pospropt=0.; */
1.265 brouard 5896: for(s1=-1; s1 <=nlstate+ndeath; s1++){
1.251 brouard 5897: for(m=-1; m <=nlstate+ndeath; m++){
1.265 brouard 5898: if(freq[s1][m][iage] !=0 ) { /* minimizing output */
1.251 brouard 5899: if(first==1){
1.265 brouard 5900: printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5901: }
1.265 brouard 5902: /* printf(" %d%d=%.0f",s1,m,freq[s1][m][iage]); */
5903: fprintf(ficlog," %d%d=%.0f",s1,m,freq[s1][m][iage]);
1.251 brouard 5904: }
1.265 brouard 5905: if(s1!=0 && m!=0)
5906: fprintf(ficresphtmfr,"<td>%.0f</td> ",freq[s1][m][iage]);
1.240 brouard 5907: }
1.265 brouard 5908: } /* end loop s1 */
1.251 brouard 5909: posproptt=0.;
1.265 brouard 5910: for(s1=1; s1 <=nlstate; s1++){
5911: posproptt += pospropt[s1];
1.251 brouard 5912: }
5913: fprintf(ficresphtmfr,"</tr>\n ");
1.265 brouard 5914: fprintf(ficresphtm,"</tr>\n");
1.335 brouard 5915: if((cptcoveff==0 && nj==1)|| nj==2 ) {
1.265 brouard 5916: if(iage <= iagemax)
5917: fprintf(ficresp,"\n");
1.240 brouard 5918: }
1.251 brouard 5919: if(first==1)
5920: printf("Others in log...\n");
5921: fprintf(ficlog,"\n");
5922: } /* end loop age iage */
1.265 brouard 5923:
1.251 brouard 5924: fprintf(ficresphtm,"<tr><th>Tot</th>");
1.265 brouard 5925: for(s1=1; s1 <=nlstate ; s1++){
1.251 brouard 5926: if(posproptt < 1.e-5){
1.265 brouard 5927: fprintf(ficresphtm,"<td>Nanq</td><td>%.0f</td><td>%.0f</td>",pospropt[s1],posproptt);
1.251 brouard 5928: }else{
1.265 brouard 5929: fprintf(ficresphtm,"<td>%.5f</td><td>%.0f</td><td>%.0f</td>",pospropt[s1]/posproptt,pospropt[s1],posproptt);
1.240 brouard 5930: }
1.226 brouard 5931: }
1.251 brouard 5932: fprintf(ficresphtm,"</tr>\n");
5933: fprintf(ficresphtm,"</table>\n");
5934: fprintf(ficresphtmfr,"</table>\n");
1.226 brouard 5935: if(posproptt < 1.e-5){
1.251 brouard 5936: fprintf(ficresphtm,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
5937: fprintf(ficresphtmfr,"\n <p><b> This combination (%d) is not valid and no result will be produced</b></p>",j1);
1.260 brouard 5938: fprintf(ficlog,"# This combination (%d) is not valid and no result will be produced\n",j1);
5939: printf("# This combination (%d) is not valid and no result will be produced\n",j1);
1.251 brouard 5940: invalidvarcomb[j1]=1;
1.226 brouard 5941: }else{
1.338 brouard 5942: fprintf(ficresphtm,"\n <p> This combination (%d) is valid and result will be produced (or no resultline).</p>",j1);
1.251 brouard 5943: invalidvarcomb[j1]=0;
1.226 brouard 5944: }
1.251 brouard 5945: fprintf(ficresphtmfr,"</table>\n");
5946: fprintf(ficlog,"\n");
5947: if(j!=0){
5948: printf("#Freqsummary: Starting values for combination j1=%d:\n", j1);
1.265 brouard 5949: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5950: for(k=1; k <=(nlstate+ndeath); k++){
5951: if (k != i) {
1.265 brouard 5952: for(jj=1; jj <=ncovmodel; jj++){ /* For counting s1 */
1.253 brouard 5953: if(jj==1){ /* Constant case (in fact cste + age) */
1.251 brouard 5954: if(j1==1){ /* All dummy covariates to zero */
5955: freq[i][k][iagemax+4]=freq[i][k][iagemax+3]; /* Stores case 0 0 0 */
5956: freq[i][i][iagemax+4]=freq[i][i][iagemax+3]; /* Stores case 0 0 0 */
1.252 brouard 5957: printf("%d%d ",i,k);
5958: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5959: printf("%12.7f ln(%.0f/%.0f)= %f, OR=%f sd=%f \n",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]),freq[i][k][iagemax+3]/freq[i][i][iagemax+3], sqrt(1/freq[i][k][iagemax+3]+1/freq[i][i][iagemax+3]));
5960: fprintf(ficlog,"%12.7f ln(%.0f/%.0f)= %12.7f \n",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
5961: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
1.251 brouard 5962: }
1.253 brouard 5963: }else if((j1==1) && (jj==2 || nagesqr==1)){ /* age or age*age parameter without covariate V4*age (to be done later) */
5964: for(iage=iagemin; iage <= iagemax+3; iage++){
5965: x[iage]= (double)iage;
5966: y[iage]= log(freq[i][k][iage]/freq[i][i][iage]);
1.265 brouard 5967: /* printf("i=%d, k=%d, s1=%d, j1=%d, jj=%d, y[%d]=%f\n",i,k,s1,j1,jj, iage, y[iage]); */
1.253 brouard 5968: }
1.268 brouard 5969: /* Some are not finite, but linreg will ignore these ages */
5970: no=0;
1.253 brouard 5971: linreg(iagemin,iagemax,&no,x,y,&a,&b,&r, &sa, &sb ); /* y= a+b*x with standard errors */
1.265 brouard 5972: pstart[s1]=b;
5973: pstart[s1-1]=a;
1.252 brouard 5974: }else if( j1!=1 && (j1==2 || (log(j1-1.)/log(2.)-(int)(log(j1-1.)/log(2.))) <0.010) && ( TvarsDind[(int)(log(j1-1.)/log(2.))+1]+2+nagesqr == jj) && Dummy[jj-2-nagesqr]==0){ /* We want only if the position, jj, in model corresponds to unique covariate equal to 1 in j1 combination */
5975: printf("j1=%d, jj=%d, (int)(log(j1-1.)/log(2.))+1=%d, TvarsDind[(int)(log(j1-1.)/log(2.))+1]=%d\n",j1, jj,(int)(log(j1-1.)/log(2.))+1,TvarsDind[(int)(log(j1-1.)/log(2.))+1]);
5976: printf("j1=%d, jj=%d, (log(j1-1.)/log(2.))+1=%f, TvarsDind[(int)(log(j1-1.)/log(2.))+1]=%d\n",j1, jj,(log(j1-1.)/log(2.))+1,TvarsDind[(int)(log(j1-1.)/log(2.))+1]);
1.265 brouard 5977: pstart[s1]= log((freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4]));
1.252 brouard 5978: printf("%d%d ",i,k);
5979: fprintf(ficlog,"%d%d ",i,k);
1.265 brouard 5980: printf("s1=%d,i=%d,k=%d,p[%d]=%12.7f ln((%.0f/%.0f)/(%.0f/%.0f))= %f, OR=%f sd=%f \n",s1,i,k,s1,p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3],freq[i][k][iagemax+4],freq[i][i][iagemax+4], log((freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4])),(freq[i][k][iagemax+3]/freq[i][i][iagemax+3])/(freq[i][k][iagemax+4]/freq[i][i][iagemax+4]), sqrt(1/freq[i][k][iagemax+3]+1/freq[i][i][iagemax+3]+1/freq[i][k][iagemax+4]+1/freq[i][i][iagemax+4]));
1.251 brouard 5981: }else{ /* Other cases, like quantitative fixed or varying covariates */
5982: ;
5983: }
5984: /* printf("%12.7f )", param[i][jj][k]); */
5985: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 5986: s1++;
1.251 brouard 5987: } /* end jj */
5988: } /* end k!= i */
5989: } /* end k */
1.265 brouard 5990: } /* end i, s1 */
1.251 brouard 5991: } /* end j !=0 */
5992: } /* end selected combination of covariate j1 */
5993: if(j==0){ /* We can estimate starting values from the occurences in each case */
5994: printf("#Freqsummary: Starting values for the constants:\n");
5995: fprintf(ficlog,"\n");
1.265 brouard 5996: for(i=1,s1=1; i <=nlstate; i++){
1.251 brouard 5997: for(k=1; k <=(nlstate+ndeath); k++){
5998: if (k != i) {
5999: printf("%d%d ",i,k);
6000: fprintf(ficlog,"%d%d ",i,k);
6001: for(jj=1; jj <=ncovmodel; jj++){
1.265 brouard 6002: pstart[s1]=p[s1]; /* Setting pstart to p values by default */
1.253 brouard 6003: if(jj==1){ /* Age has to be done */
1.265 brouard 6004: pstart[s1]= log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]);
6005: printf("%12.7f ln(%.0f/%.0f)= %12.7f ",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
6006: fprintf(ficlog,"%12.7f ln(%.0f/%.0f)= %12.7f ",p[s1],freq[i][k][iagemax+3],freq[i][i][iagemax+3], log(freq[i][k][iagemax+3]/freq[i][i][iagemax+3]));
1.251 brouard 6007: }
6008: /* printf("%12.7f )", param[i][jj][k]); */
6009: /* fprintf(ficlog,"%12.7f )", param[i][jj][k]); */
1.265 brouard 6010: s1++;
1.250 brouard 6011: }
1.251 brouard 6012: printf("\n");
6013: fprintf(ficlog,"\n");
1.250 brouard 6014: }
6015: }
1.284 brouard 6016: } /* end of state i */
1.251 brouard 6017: printf("#Freqsummary\n");
6018: fprintf(ficlog,"\n");
1.265 brouard 6019: for(s1=-1; s1 <=nlstate+ndeath; s1++){
6020: for(s2=-1; s2 <=nlstate+ndeath; s2++){
6021: /* param[i]|j][k]= freq[s1][s2][iagemax+3] */
6022: printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
6023: fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]);
6024: /* if(freq[s1][s2][iage] !=0 ) { /\* minimizing output *\/ */
6025: /* printf(" %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
6026: /* fprintf(ficlog," %d%d=%.0f",s1,s2,freq[s1][s2][iagemax+3]); */
1.251 brouard 6027: /* } */
6028: }
1.265 brouard 6029: } /* end loop s1 */
1.251 brouard 6030:
6031: printf("\n");
6032: fprintf(ficlog,"\n");
6033: } /* end j=0 */
1.249 brouard 6034: } /* end j */
1.252 brouard 6035:
1.253 brouard 6036: if(mle == -2){ /* We want to use these values as starting values */
1.252 brouard 6037: for(i=1, jk=1; i <=nlstate; i++){
6038: for(j=1; j <=nlstate+ndeath; j++){
6039: if(j!=i){
6040: /*ca[0]= k+'a'-1;ca[1]='\0';*/
6041: printf("%1d%1d",i,j);
6042: fprintf(ficparo,"%1d%1d",i,j);
6043: for(k=1; k<=ncovmodel;k++){
6044: /* printf(" %lf",param[i][j][k]); */
6045: /* fprintf(ficparo," %lf",param[i][j][k]); */
6046: p[jk]=pstart[jk];
6047: printf(" %f ",pstart[jk]);
6048: fprintf(ficparo," %f ",pstart[jk]);
6049: jk++;
6050: }
6051: printf("\n");
6052: fprintf(ficparo,"\n");
6053: }
6054: }
6055: }
6056: } /* end mle=-2 */
1.226 brouard 6057: dateintmean=dateintsum/k2cpt;
1.296 brouard 6058: date2dmy(dateintmean,&jintmean,&mintmean,&aintmean);
1.240 brouard 6059:
1.226 brouard 6060: fclose(ficresp);
6061: fclose(ficresphtm);
6062: fclose(ficresphtmfr);
1.283 brouard 6063: free_vector(idq,1,nqfveff);
1.226 brouard 6064: free_vector(meanq,1,nqfveff);
1.284 brouard 6065: free_vector(stdq,1,nqfveff);
1.226 brouard 6066: free_matrix(meanqt,1,lastpass,1,nqtveff);
1.253 brouard 6067: free_vector(x, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
6068: free_vector(y, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.251 brouard 6069: free_ma3x(freq,-5,nlstate+ndeath,-5,nlstate+ndeath, iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6070: free_vector(pospropt,1,nlstate);
6071: free_vector(posprop,1,nlstate);
1.251 brouard 6072: free_matrix(prop,1,nlstate,iagemin-AGEMARGE, iagemax+4+AGEMARGE);
1.226 brouard 6073: free_vector(pp,1,nlstate);
6074: /* End of freqsummary */
6075: }
1.126 brouard 6076:
1.268 brouard 6077: /* Simple linear regression */
6078: int linreg(int ifi, int ila, int *no, const double x[], const double y[], double* a, double* b, double* r, double* sa, double * sb) {
6079:
6080: /* y=a+bx regression */
6081: double sumx = 0.0; /* sum of x */
6082: double sumx2 = 0.0; /* sum of x**2 */
6083: double sumxy = 0.0; /* sum of x * y */
6084: double sumy = 0.0; /* sum of y */
6085: double sumy2 = 0.0; /* sum of y**2 */
6086: double sume2 = 0.0; /* sum of square or residuals */
6087: double yhat;
6088:
6089: double denom=0;
6090: int i;
6091: int ne=*no;
6092:
6093: for ( i=ifi, ne=0;i<=ila;i++) {
6094: if(!isfinite(x[i]) || !isfinite(y[i])){
6095: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6096: continue;
6097: }
6098: ne=ne+1;
6099: sumx += x[i];
6100: sumx2 += x[i]*x[i];
6101: sumxy += x[i] * y[i];
6102: sumy += y[i];
6103: sumy2 += y[i]*y[i];
6104: denom = (ne * sumx2 - sumx*sumx);
6105: /* printf("ne=%d, i=%d,x[%d]=%f, y[%d]=%f sumx=%f, sumx2=%f, sumxy=%f, sumy=%f, sumy2=%f, denom=%f\n",ne,i,i,x[i],i,y[i], sumx, sumx2,sumxy, sumy, sumy2,denom); */
6106: }
6107:
6108: denom = (ne * sumx2 - sumx*sumx);
6109: if (denom == 0) {
6110: // vertical, slope m is infinity
6111: *b = INFINITY;
6112: *a = 0;
6113: if (r) *r = 0;
6114: return 1;
6115: }
6116:
6117: *b = (ne * sumxy - sumx * sumy) / denom;
6118: *a = (sumy * sumx2 - sumx * sumxy) / denom;
6119: if (r!=NULL) {
6120: *r = (sumxy - sumx * sumy / ne) / /* compute correlation coeff */
6121: sqrt((sumx2 - sumx*sumx/ne) *
6122: (sumy2 - sumy*sumy/ne));
6123: }
6124: *no=ne;
6125: for ( i=ifi, ne=0;i<=ila;i++) {
6126: if(!isfinite(x[i]) || !isfinite(y[i])){
6127: /* printf(" x[%d]=%f, y[%d]=%f\n",i,x[i],i,y[i]); */
6128: continue;
6129: }
6130: ne=ne+1;
6131: yhat = y[i] - *a -*b* x[i];
6132: sume2 += yhat * yhat ;
6133:
6134: denom = (ne * sumx2 - sumx*sumx);
6135: /* printf("ne=%d, i=%d,x[%d]=%f, y[%d]=%f sumx=%f, sumx2=%f, sumxy=%f, sumy=%f, sumy2=%f, denom=%f\n",ne,i,i,x[i],i,y[i], sumx, sumx2,sumxy, sumy, sumy2,denom); */
6136: }
6137: *sb = sqrt(sume2/(double)(ne-2)/(sumx2 - sumx * sumx /(double)ne));
6138: *sa= *sb * sqrt(sumx2/ne);
6139:
6140: return 0;
6141: }
6142:
1.126 brouard 6143: /************ Prevalence ********************/
1.227 brouard 6144: void prevalence(double ***probs, double agemin, double agemax, int **s, double **agev, int nlstate, int imx, int *Tvar, int **nbcode, int *ncodemax,double **mint,double **anint, double dateprev1,double dateprev2, int firstpass, int lastpass)
6145: {
6146: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
6147: in each health status at the date of interview (if between dateprev1 and dateprev2).
6148: We still use firstpass and lastpass as another selection.
6149: */
1.126 brouard 6150:
1.227 brouard 6151: int i, m, jk, j1, bool, z1,j, iv;
6152: int mi; /* Effective wave */
6153: int iage;
6154: double agebegin, ageend;
6155:
6156: double **prop;
6157: double posprop;
6158: double y2; /* in fractional years */
6159: int iagemin, iagemax;
6160: int first; /** to stop verbosity which is redirected to log file */
6161:
6162: iagemin= (int) agemin;
6163: iagemax= (int) agemax;
6164: /*pp=vector(1,nlstate);*/
1.251 brouard 6165: prop=matrix(1,nlstate,iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6166: /* freq=ma3x(-1,nlstate+ndeath,-1,nlstate+ndeath,iagemin,iagemax+3);*/
6167: j1=0;
1.222 brouard 6168:
1.227 brouard 6169: /*j=cptcoveff;*/
6170: if (cptcovn<1) {j=1;ncodemax[1]=1;}
1.222 brouard 6171:
1.288 brouard 6172: first=0;
1.335 brouard 6173: for(j1=1; j1<= (int) pow(2,cptcoveff);j1++){ /* For each combination of simple dummy covariates */
1.227 brouard 6174: for (i=1; i<=nlstate; i++)
1.251 brouard 6175: for(iage=iagemin-AGEMARGE; iage <= iagemax+4+AGEMARGE; iage++)
1.227 brouard 6176: prop[i][iage]=0.0;
6177: printf("Prevalence combination of varying and fixed dummies %d\n",j1);
6178: /* fprintf(ficlog," V%d=%d ",Tvaraff[j1],nbcode[Tvaraff[j1]][codtabm(k,j1)]); */
6179: fprintf(ficlog,"Prevalence combination of varying and fixed dummies %d\n",j1);
6180:
6181: for (i=1; i<=imx; i++) { /* Each individual */
6182: bool=1;
6183: /* for(m=firstpass; m<=lastpass; m++){/\* Other selection (we can limit to certain interviews*\/ */
6184: for(mi=1; mi<wav[i];mi++){ /* For this wave too look where individual can be counted V4=0 V3=0 */
6185: m=mw[mi][i];
6186: /* Tmodelind[z1]=k is the position of the varying covariate in the model, but which # within 1 to ntv? */
6187: /* Tvar[Tmodelind[z1]] is the n of Vn; n-ncovcol-nqv is the first time varying covariate or iv */
6188: for (z1=1; z1<=cptcoveff; z1++){
6189: if( Fixed[Tmodelind[z1]]==1){
1.341 brouard 6190: iv= Tvar[Tmodelind[z1]];/* because cotvar starts now at first ncovcol+nqv+ (1 to nqtv) */
1.332 brouard 6191: if (cotvar[m][iv][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) /* iv=1 to ntv, right modality */
1.227 brouard 6192: bool=0;
6193: }else if( Fixed[Tmodelind[z1]]== 0) /* fixed */
1.332 brouard 6194: if (covar[Tvaraff[z1]][i]!= nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]) {
1.227 brouard 6195: bool=0;
6196: }
6197: }
6198: if(bool==1){ /* Otherwise we skip that wave/person */
6199: agebegin=agev[m][i]; /* Age at beginning of wave before transition*/
6200: /* ageend=agev[m][i]+(dh[m][i])*stepm/YEARM; /\* Age at end of wave and transition *\/ */
6201: if(m >=firstpass && m <=lastpass){
6202: y2=anint[m][i]+(mint[m][i]/12.); /* Fractional date in year */
6203: if ((y2>=dateprev1) && (y2<=dateprev2)) { /* Here is the main selection (fractional years) */
6204: if(agev[m][i]==0) agev[m][i]=iagemax+1;
6205: if(agev[m][i]==1) agev[m][i]=iagemax+2;
1.251 brouard 6206: if((int)agev[m][i] <iagemin-AGEMARGE || (int)agev[m][i] >iagemax+4+AGEMARGE){
1.227 brouard 6207: printf("Error on individual # %d agev[m][i]=%f <%d-%d or > %d+3+%d m=%d; either change agemin or agemax or fix data\n",i, agev[m][i],iagemin,AGEMARGE, iagemax,AGEMARGE,m);
6208: exit(1);
6209: }
6210: if (s[m][i]>0 && s[m][i]<=nlstate) {
6211: /*if(i>4620) printf(" i=%d m=%d s[m][i]=%d (int)agev[m][i]=%d weight[i]=%f prop=%f\n",i,m,s[m][i],(int)agev[m][m],weight[i],prop[s[m][i]][(int)agev[m][i]]);*/
6212: prop[s[m][i]][(int)agev[m][i]] += weight[i];/* At age of beginning of transition, where status is known */
6213: prop[s[m][i]][iagemax+3] += weight[i];
6214: } /* end valid statuses */
6215: } /* end selection of dates */
6216: } /* end selection of waves */
6217: } /* end bool */
6218: } /* end wave */
6219: } /* end individual */
6220: for(i=iagemin; i <= iagemax+3; i++){
6221: for(jk=1,posprop=0; jk <=nlstate ; jk++) {
6222: posprop += prop[jk][i];
6223: }
6224:
6225: for(jk=1; jk <=nlstate ; jk++){
6226: if( i <= iagemax){
6227: if(posprop>=1.e-5){
6228: probs[i][jk][j1]= prop[jk][i]/posprop;
6229: } else{
1.288 brouard 6230: if(!first){
6231: first=1;
1.266 brouard 6232: printf("Warning Observed prevalence doesn't sum to 1 for state %d: probs[%d][%d][%d]=%lf because of lack of cases\nSee others in log file...\n",jk,i,jk, j1,probs[i][jk][j1]);
6233: }else{
1.288 brouard 6234: fprintf(ficlog,"Warning Observed prevalence doesn't sum to 1 for state %d: probs[%d][%d][%d]=%lf because of lack of cases.\n",jk,i,jk, j1,probs[i][jk][j1]);
1.227 brouard 6235: }
6236: }
6237: }
6238: }/* end jk */
6239: }/* end i */
1.222 brouard 6240: /*} *//* end i1 */
1.227 brouard 6241: } /* end j1 */
1.222 brouard 6242:
1.227 brouard 6243: /* free_ma3x(freq,-1,nlstate+ndeath,-1,nlstate+ndeath, iagemin, iagemax+3);*/
6244: /*free_vector(pp,1,nlstate);*/
1.251 brouard 6245: free_matrix(prop,1,nlstate, iagemin-AGEMARGE,iagemax+4+AGEMARGE);
1.227 brouard 6246: } /* End of prevalence */
1.126 brouard 6247:
6248: /************* Waves Concatenation ***************/
6249:
6250: void concatwav(int wav[], int **dh, int **bh, int **mw, int **s, double *agedc, double **agev, int firstpass, int lastpass, int imx, int nlstate, int stepm)
6251: {
1.298 brouard 6252: /* Concatenates waves: wav[i] is the number of effective (useful waves in the sense that a non interview is useless) of individual i.
1.126 brouard 6253: Death is a valid wave (if date is known).
6254: mw[mi][i] is the mi (mi=1 to wav[i]) effective wave of individual i
6255: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
1.298 brouard 6256: and mw[mi+1][i]. dh depends on stepm. s[m][i] exists for any wave from firstpass to lastpass
1.227 brouard 6257: */
1.126 brouard 6258:
1.224 brouard 6259: int i=0, mi=0, m=0, mli=0;
1.126 brouard 6260: /* int j, k=0,jk, ju, jl,jmin=1e+5, jmax=-1;
6261: double sum=0., jmean=0.;*/
1.224 brouard 6262: int first=0, firstwo=0, firsthree=0, firstfour=0, firstfiv=0;
1.126 brouard 6263: int j, k=0,jk, ju, jl;
6264: double sum=0.;
6265: first=0;
1.214 brouard 6266: firstwo=0;
1.217 brouard 6267: firsthree=0;
1.218 brouard 6268: firstfour=0;
1.164 brouard 6269: jmin=100000;
1.126 brouard 6270: jmax=-1;
6271: jmean=0.;
1.224 brouard 6272:
6273: /* Treating live states */
1.214 brouard 6274: for(i=1; i<=imx; i++){ /* For simple cases and if state is death */
1.224 brouard 6275: mi=0; /* First valid wave */
1.227 brouard 6276: mli=0; /* Last valid wave */
1.309 brouard 6277: m=firstpass; /* Loop on waves */
6278: while(s[m][i] <= nlstate){ /* a live state or unknown state */
1.227 brouard 6279: if(m >firstpass && s[m][i]==s[m-1][i] && mint[m][i]==mint[m-1][i] && anint[m][i]==anint[m-1][i]){/* Two succesive identical information on wave m */
6280: mli=m-1;/* mw[++mi][i]=m-1; */
6281: }else if(s[m][i]>=1 || s[m][i]==-4 || s[m][i]==-5){ /* Since 0.98r4 if status=-2 vital status is really unknown, wave should be skipped */
1.309 brouard 6282: mw[++mi][i]=m; /* Valid wave: incrementing mi and updating mi; mw[mi] is the wave number of mi_th valid transition */
1.227 brouard 6283: mli=m;
1.224 brouard 6284: } /* else might be a useless wave -1 and mi is not incremented and mw[mi] not updated */
6285: if(m < lastpass){ /* m < lastpass, standard case */
1.227 brouard 6286: m++; /* mi gives the "effective" current wave, m the current wave, go to next wave by incrementing m */
1.216 brouard 6287: }
1.309 brouard 6288: else{ /* m = lastpass, eventual special issue with warning */
1.224 brouard 6289: #ifdef UNKNOWNSTATUSNOTCONTRIBUTING
1.227 brouard 6290: break;
1.224 brouard 6291: #else
1.317 brouard 6292: if(s[m][i]==-1 && (int) andc[i] == 9999 && (int)anint[m][i] != 9999){ /* no death date and known date of interview, case -2 (vital status unknown is warned later */
1.227 brouard 6293: if(firsthree == 0){
1.302 brouard 6294: printf("Information! Unknown status for individual %ld line=%d occurred at last wave %d at known date %d/%d. Please, check if your unknown date of death %d/%d means a live state %d at wave %d. This case(%d)/wave(%d) contributes to the likelihood as 1-p_{%d%d} .\nOthers in log file only\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], (int) moisdc[i], (int) andc[i], s[m][i], m, i, m, s[m][i], nlstate+ndeath);
1.227 brouard 6295: firsthree=1;
1.317 brouard 6296: }else if(firsthree >=1 && firsthree < 10){
6297: fprintf(ficlog,"Information! Unknown status for individual %ld line=%d occurred at last wave %d at known date %d/%d. Please, check if your unknown date of death %d/%d means a live state %d at wave %d. This case(%d)/wave(%d) contributes to the likelihood as 1-p_{%d%d} .\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], (int) moisdc[i], (int) andc[i], s[m][i], m, i, m, s[m][i], nlstate+ndeath);
6298: firsthree++;
6299: }else if(firsthree == 10){
6300: printf("Information, too many Information flags: no more reported to log either\n");
6301: fprintf(ficlog,"Information, too many Information flags: no more reported to log either\n");
6302: firsthree++;
6303: }else{
6304: firsthree++;
1.227 brouard 6305: }
1.309 brouard 6306: mw[++mi][i]=m; /* Valid transition with unknown status */
1.227 brouard 6307: mli=m;
6308: }
6309: if(s[m][i]==-2){ /* Vital status is really unknown */
6310: nbwarn++;
1.309 brouard 6311: if((int)anint[m][i] == 9999){ /* Has the vital status really been verified?not a transition */
1.227 brouard 6312: printf("Warning! Vital status for individual %ld (line=%d) at last wave %d interviewed at date %d/%d is unknown %d. Please, check if the vital status and the date of death %d/%d are really unknown. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\nOthers in log file only\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], (int) moisdc[i], (int) andc[i], i, m);
6313: fprintf(ficlog,"Warning! Vital status for individual %ld (line=%d) at last wave %d interviewed at date %d/%d is unknown %d. Please, check if the vital status and the date of death %d/%d are really unknown. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\n",num[i],i,lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], (int) moisdc[i], (int) andc[i], i, m);
6314: }
6315: break;
6316: }
6317: break;
1.224 brouard 6318: #endif
1.227 brouard 6319: }/* End m >= lastpass */
1.126 brouard 6320: }/* end while */
1.224 brouard 6321:
1.227 brouard 6322: /* mi is the last effective wave, m is lastpass, mw[j][i] gives the # of j-th effective wave for individual i */
1.216 brouard 6323: /* After last pass */
1.224 brouard 6324: /* Treating death states */
1.214 brouard 6325: if (s[m][i] > nlstate){ /* In a death state */
1.227 brouard 6326: /* if( mint[m][i]==mdc[m][i] && anint[m][i]==andc[m][i]){ /\* same date of death and date of interview *\/ */
6327: /* } */
1.126 brouard 6328: mi++; /* Death is another wave */
6329: /* if(mi==0) never been interviewed correctly before death */
1.227 brouard 6330: /* Only death is a correct wave */
1.126 brouard 6331: mw[mi][i]=m;
1.257 brouard 6332: } /* else not in a death state */
1.224 brouard 6333: #ifndef DISPATCHINGKNOWNDEATHAFTERLASTWAVE
1.257 brouard 6334: else if ((int) andc[i] != 9999) { /* Date of death is known */
1.218 brouard 6335: if ((int)anint[m][i]!= 9999) { /* date of last interview is known */
1.309 brouard 6336: if((andc[i]+moisdc[i]/12.) <=(anint[m][i]+mint[m][i]/12.)){ /* month of death occured before last wave month and status should have been death instead of -1 */
1.227 brouard 6337: nbwarn++;
6338: if(firstfiv==0){
1.309 brouard 6339: printf("Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d, interviewed on %d/%d and should have been coded as death instead of '%d'. This case (%d)/wave (%d) is contributing to likelihood.\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.227 brouard 6340: firstfiv=1;
6341: }else{
1.309 brouard 6342: fprintf(ficlog,"Warning! Death for individual %ld line=%d occurred at %d/%d before last wave %d, interviewed on %d/%d and should have been coded as death instead of '%d'. This case (%d)/wave (%d) is contributing to likelihood.\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.227 brouard 6343: }
1.309 brouard 6344: s[m][i]=nlstate+1; /* Fixing the status as death. Be careful if multiple death states */
6345: }else{ /* Month of Death occured afer last wave month, potential bias */
1.227 brouard 6346: nberr++;
6347: if(firstwo==0){
1.309 brouard 6348: printf("Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d with status %d. Potential bias if other individuals are still alive on this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood. Please add a new fictitious wave at the date of last vital status scan, with a dead status. See documentation\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.227 brouard 6349: firstwo=1;
6350: }
1.309 brouard 6351: fprintf(ficlog,"Error! Death for individual %ld line=%d occurred at %d/%d after last wave %d interviewed at %d/%d with status %d. Potential bias if other individuals are still alive on this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood. Please add a new fictitious wave at the date of last vital status scan, with a dead status. See documentation\n\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.227 brouard 6352: }
1.257 brouard 6353: }else{ /* if date of interview is unknown */
1.227 brouard 6354: /* death is known but not confirmed by death status at any wave */
6355: if(firstfour==0){
1.309 brouard 6356: printf("Error! Death for individual %ld line=%d occurred %d/%d but not confirmed by any death status for any wave, including last wave %d at unknown date %d/%d with status %d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\nOthers in log file only\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.227 brouard 6357: firstfour=1;
6358: }
1.309 brouard 6359: fprintf(ficlog,"Error! Death for individual %ld line=%d occurred %d/%d but not confirmed by any death status for any wave, including last wave %d at unknown date %d/%d with status %d. Potential bias if other individuals are still alive at this date but ignored. This case (%d)/wave (%d) is skipped, no contribution to likelihood.\n",num[i],i,(int) moisdc[i], (int) andc[i], lastpass,(int)mint[m][i],(int)anint[m][i], s[m][i], i,m );
1.214 brouard 6360: }
1.224 brouard 6361: } /* end if date of death is known */
6362: #endif
1.309 brouard 6363: wav[i]=mi; /* mi should be the last effective wave (or mli), */
6364: /* wav[i]=mw[mi][i]; */
1.126 brouard 6365: if(mi==0){
6366: nbwarn++;
6367: if(first==0){
1.227 brouard 6368: printf("Warning! No valid information for individual %ld line=%d (skipped) and may be others, see log file\n",num[i],i);
6369: first=1;
1.126 brouard 6370: }
6371: if(first==1){
1.227 brouard 6372: fprintf(ficlog,"Warning! No valid information for individual %ld line=%d (skipped)\n",num[i],i);
1.126 brouard 6373: }
6374: } /* end mi==0 */
6375: } /* End individuals */
1.214 brouard 6376: /* wav and mw are no more changed */
1.223 brouard 6377:
1.317 brouard 6378: printf("Information, you have to check %d informations which haven't been logged!\n",firsthree);
6379: fprintf(ficlog,"Information, you have to check %d informations which haven't been logged!\n",firsthree);
6380:
6381:
1.126 brouard 6382: for(i=1; i<=imx; i++){
6383: for(mi=1; mi<wav[i];mi++){
6384: if (stepm <=0)
1.227 brouard 6385: dh[mi][i]=1;
1.126 brouard 6386: else{
1.260 brouard 6387: if (s[mw[mi+1][i]][i] > nlstate) { /* A death, but what if date is unknown? */
1.227 brouard 6388: if (agedc[i] < 2*AGESUP) {
6389: j= rint(agedc[i]*12-agev[mw[mi][i]][i]*12);
6390: if(j==0) j=1; /* Survives at least one month after exam */
6391: else if(j<0){
6392: nberr++;
6393: printf("Error! Negative delay (%d to death) between waves %d and %d of individual %ld at line %d who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);
6394: j=1; /* Temporary Dangerous patch */
6395: printf(" We assumed that the date of interview was correct (and not the date of death) and postponed the death %d month(s) (one stepm) after the interview. You MUST fix the contradiction between dates.\n",stepm);
6396: fprintf(ficlog,"Error! Negative delay (%d to death) between waves %d and %d of individual %ld at line %d who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);
6397: fprintf(ficlog," We assumed that the date of interview was correct (and not the date of death) and postponed the death %d month(s) (one stepm) after the interview. You MUST fix the contradiction between dates.\n",stepm);
6398: }
6399: k=k+1;
6400: if (j >= jmax){
6401: jmax=j;
6402: ijmax=i;
6403: }
6404: if (j <= jmin){
6405: jmin=j;
6406: ijmin=i;
6407: }
6408: sum=sum+j;
6409: /*if (j<0) printf("j=%d num=%d \n",j,i);*/
6410: /* printf("%d %d %d %d\n", s[mw[mi][i]][i] ,s[mw[mi+1][i]][i],j,i);*/
6411: }
6412: }
6413: else{
6414: j= rint( (agev[mw[mi+1][i]][i]*12 - agev[mw[mi][i]][i]*12));
1.126 brouard 6415: /* if (j<0) printf("%d %lf %lf %d %d %d\n", i,agev[mw[mi+1][i]][i], agev[mw[mi][i]][i],j,s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]); */
1.223 brouard 6416:
1.227 brouard 6417: k=k+1;
6418: if (j >= jmax) {
6419: jmax=j;
6420: ijmax=i;
6421: }
6422: else if (j <= jmin){
6423: jmin=j;
6424: ijmin=i;
6425: }
6426: /* if (j<10) printf("j=%d jmin=%d num=%d ",j,jmin,i); */
6427: /*printf("%d %lf %d %d %d\n", i,agev[mw[mi][i]][i],j,s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);*/
6428: if(j<0){
6429: nberr++;
6430: printf("Error! Negative delay (%d) between waves %d and %d of individual %ld at line %d who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);
6431: fprintf(ficlog,"Error! Negative delay (%d) between waves %d and %d of individual %ld at line %d who is aged %.1f with statuses from %d to %d\n ",j,mw[mi][i],mw[mi+1][i],num[i], i,agev[mw[mi][i]][i],s[mw[mi][i]][i] ,s[mw[mi+1][i]][i]);
6432: }
6433: sum=sum+j;
6434: }
6435: jk= j/stepm;
6436: jl= j -jk*stepm;
6437: ju= j -(jk+1)*stepm;
6438: if(mle <=1){ /* only if we use a the linear-interpoloation pseudo-likelihood */
6439: if(jl==0){
6440: dh[mi][i]=jk;
6441: bh[mi][i]=0;
6442: }else{ /* We want a negative bias in order to only have interpolation ie
6443: * to avoid the price of an extra matrix product in likelihood */
6444: dh[mi][i]=jk+1;
6445: bh[mi][i]=ju;
6446: }
6447: }else{
6448: if(jl <= -ju){
6449: dh[mi][i]=jk;
6450: bh[mi][i]=jl; /* bias is positive if real duration
6451: * is higher than the multiple of stepm and negative otherwise.
6452: */
6453: }
6454: else{
6455: dh[mi][i]=jk+1;
6456: bh[mi][i]=ju;
6457: }
6458: if(dh[mi][i]==0){
6459: dh[mi][i]=1; /* At least one step */
6460: bh[mi][i]=ju; /* At least one step */
6461: /* printf(" bh=%d ju=%d jl=%d dh=%d jk=%d stepm=%d %d\n",bh[mi][i],ju,jl,dh[mi][i],jk,stepm,i);*/
6462: }
6463: } /* end if mle */
1.126 brouard 6464: }
6465: } /* end wave */
6466: }
6467: jmean=sum/k;
6468: printf("Delay (in months) between two waves Min=%d (for indiviudal %ld) Max=%d (%ld) Mean=%f\n\n ",jmin, num[ijmin], jmax, num[ijmax], jmean);
1.141 brouard 6469: fprintf(ficlog,"Delay (in months) between two waves Min=%d (for indiviudal %d) Max=%d (%d) Mean=%f\n\n ",jmin, ijmin, jmax, ijmax, jmean);
1.227 brouard 6470: }
1.126 brouard 6471:
6472: /*********** Tricode ****************************/
1.220 brouard 6473: void tricode(int *cptcov, int *Tvar, int **nbcode, int imx, int *Ndum)
1.242 brouard 6474: {
6475: /**< Uses cptcovn+2*cptcovprod as the number of covariates */
6476: /* Tvar[i]=atoi(stre); find 'n' in Vn and stores in Tvar. If model=V2+V1 Tvar[1]=2 and Tvar[2]=1
6477: * Boring subroutine which should only output nbcode[Tvar[j]][k]
6478: * Tvar[5] in V2+V1+V3*age+V2*V4 is 4 (V4) even it is a time varying or quantitative variable
6479: * nbcode[Tvar[5]][1]= nbcode[4][1]=0, nbcode[4][2]=1 (usually);
6480: */
1.130 brouard 6481:
1.242 brouard 6482: int ij=1, k=0, j=0, i=0, maxncov=NCOVMAX;
6483: int modmaxcovj=0; /* Modality max of covariates j */
6484: int cptcode=0; /* Modality max of covariates j */
6485: int modmincovj=0; /* Modality min of covariates j */
1.145 brouard 6486:
6487:
1.242 brouard 6488: /* cptcoveff=0; */
6489: /* *cptcov=0; */
1.126 brouard 6490:
1.242 brouard 6491: for (k=1; k <= maxncov; k++) ncodemax[k]=0; /* Horrible constant again replaced by NCOVMAX */
1.285 brouard 6492: for (k=1; k <= maxncov; k++)
6493: for(j=1; j<=2; j++)
6494: nbcode[k][j]=0; /* Valgrind */
1.126 brouard 6495:
1.242 brouard 6496: /* Loop on covariates without age and products and no quantitative variable */
1.335 brouard 6497: for (k=1; k<=cptcovt; k++) { /* cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
1.242 brouard 6498: for (j=-1; (j < maxncov); j++) Ndum[j]=0;
1.343 brouard 6499: /* printf("Testing k=%d, cptcovt=%d\n",k, cptcovt); */
1.349 brouard 6500: if(Dummy[k]==0 && Typevar[k] !=1 && Typevar[k] != 3 && Typevar[k] != 2){ /* Dummy covariate and not age product nor fixed product */
1.242 brouard 6501: switch(Fixed[k]) {
6502: case 0: /* Testing on fixed dummy covariate, simple or product of fixed */
1.311 brouard 6503: modmaxcovj=0;
6504: modmincovj=0;
1.242 brouard 6505: for (i=1; i<=imx; i++) { /* Loop on individuals: reads the data file to get the maximum value of the modality of this covariate Vj*/
1.339 brouard 6506: /* printf("Waiting for error tricode Tvar[%d]=%d i=%d (int)(covar[Tvar[k]][i]=%d\n",k,Tvar[k], i, (int)(covar[Tvar[k]][i])); */
1.242 brouard 6507: ij=(int)(covar[Tvar[k]][i]);
6508: /* ij=0 or 1 or -1. Value of the covariate Tvar[j] for individual i
6509: * If product of Vn*Vm, still boolean *:
6510: * If it was coded 1, 2, 3, 4 should be splitted into 3 boolean variables
6511: * 1 => 0 0 0, 2 => 0 0 1, 3 => 0 1 1, 4=1 0 0 */
6512: /* Finds for covariate j, n=Tvar[j] of Vn . ij is the
6513: modality of the nth covariate of individual i. */
6514: if (ij > modmaxcovj)
6515: modmaxcovj=ij;
6516: else if (ij < modmincovj)
6517: modmincovj=ij;
1.287 brouard 6518: if (ij <0 || ij >1 ){
1.311 brouard 6519: printf("ERROR, IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6520: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=-1, individual %d will be skipped.\n",Tvar[k],i);
6521: fflush(ficlog);
6522: exit(1);
1.287 brouard 6523: }
6524: if ((ij < -1) || (ij > NCOVMAX)){
1.242 brouard 6525: printf( "Error: minimal is less than -1 or maximal is bigger than %d. Exiting. \n", NCOVMAX );
6526: exit(1);
6527: }else
6528: Ndum[ij]++; /*counts and stores the occurence of this modality 0, 1, -1*/
6529: /* If coded 1, 2, 3 , counts the number of 1 Ndum[1], number of 2, Ndum[2], etc */
6530: /*printf("i=%d ij=%d Ndum[ij]=%d imx=%d",i,ij,Ndum[ij],imx);*/
6531: /* getting the maximum value of the modality of the covariate
6532: (should be 0 or 1 now) Tvar[j]. If V=sex and male is coded 0 and
6533: female ies 1, then modmaxcovj=1.
6534: */
6535: } /* end for loop on individuals i */
6536: printf(" Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6537: fprintf(ficlog," Minimal and maximal values of %d th (fixed) covariate V%d: min=%d max=%d \n", k, Tvar[k], modmincovj, modmaxcovj);
6538: cptcode=modmaxcovj;
6539: /* Ndum[0] = frequency of 0 for model-covariate j, Ndum[1] frequency of 1 etc. */
6540: /*for (i=0; i<=cptcode; i++) {*/
6541: for (j=modmincovj; j<=modmaxcovj; j++) { /* j=-1 ? 0 and 1*//* For each value j of the modality of model-cov k */
6542: printf("Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6543: fprintf(ficlog, "Frequencies of (fixed) covariate %d ie V%d with value %d: %d\n", k, Tvar[k], j, Ndum[j]);
6544: if( Ndum[j] != 0 ){ /* Counts if nobody answered modality j ie empty modality, we skip it and reorder */
6545: if( j != -1){
6546: ncodemax[k]++; /* ncodemax[k]= Number of modalities of the k th
6547: covariate for which somebody answered excluding
6548: undefined. Usually 2: 0 and 1. */
6549: }
6550: ncodemaxwundef[k]++; /* ncodemax[j]= Number of modalities of the k th
6551: covariate for which somebody answered including
6552: undefined. Usually 3: -1, 0 and 1. */
6553: } /* In fact ncodemax[k]=2 (dichotom. variables only) but it could be more for
6554: * historical reasons: 3 if coded 1, 2, 3 and 4 and Ndum[2]=0 */
6555: } /* Ndum[-1] number of undefined modalities */
1.231 brouard 6556:
1.242 brouard 6557: /* j is a covariate, n=Tvar[j] of Vn; Fills nbcode */
6558: /* For covariate j, modalities could be 1, 2, 3, 4, 5, 6, 7. */
6559: /* If Ndum[1]=0, Ndum[2]=0, Ndum[3]= 635, Ndum[4]=0, Ndum[5]=0, Ndum[6]=27, Ndum[7]=125; */
6560: /* modmincovj=3; modmaxcovj = 7; */
6561: /* There are only 3 modalities non empty 3, 6, 7 (or 2 if 27 is too few) : ncodemax[j]=3; */
6562: /* which will be coded 0, 1, 2 which in binary on 2=3-1 digits are 0=00 1=01, 2=10; */
6563: /* defining two dummy variables: variables V1_1 and V1_2.*/
6564: /* nbcode[Tvar[j]][ij]=k; */
6565: /* nbcode[Tvar[j]][1]=0; */
6566: /* nbcode[Tvar[j]][2]=1; */
6567: /* nbcode[Tvar[j]][3]=2; */
6568: /* To be continued (not working yet). */
6569: ij=0; /* ij is similar to i but can jump over null modalities */
1.287 brouard 6570:
6571: /* for (i=modmincovj; i<=modmaxcovj; i++) { */ /* i= 1 to 2 for dichotomous, or from 1 to 3 or from -1 or 0 to 1 currently*/
6572: /* Skipping the case of missing values by reducing nbcode to 0 and 1 and not -1, 0, 1 */
6573: /* model=V1+V2+V3, if V2=-1, 0 or 1, then nbcode[2][1]=0 and nbcode[2][2]=1 instead of
6574: * nbcode[2][1]=-1, nbcode[2][2]=0 and nbcode[2][3]=1 */
6575: /*, could be restored in the future */
6576: for (i=0; i<=1; i++) { /* i= 1 to 2 for dichotomous, or from 1 to 3 or from -1 or 0 to 1 currently*/
1.242 brouard 6577: if (Ndum[i] == 0) { /* If nobody responded to this modality k */
6578: break;
6579: }
6580: ij++;
1.287 brouard 6581: nbcode[Tvar[k]][ij]=i; /* stores the original value of modality i in an array nbcode, ij modality from 1 to last non-nul modality. nbcode[1][1]=0 nbcode[1][2]=1 . Could be -1*/
1.242 brouard 6582: cptcode = ij; /* New max modality for covar j */
6583: } /* end of loop on modality i=-1 to 1 or more */
6584: break;
6585: case 1: /* Testing on varying covariate, could be simple and
6586: * should look at waves or product of fixed *
6587: * varying. No time to test -1, assuming 0 and 1 only */
6588: ij=0;
6589: for(i=0; i<=1;i++){
6590: nbcode[Tvar[k]][++ij]=i;
6591: }
6592: break;
6593: default:
6594: break;
6595: } /* end switch */
6596: } /* end dummy test */
1.349 brouard 6597: if(Dummy[k]==1 && Typevar[k] !=1 && Typevar[k] !=3 && Fixed ==0){ /* Fixed Quantitative covariate and not age product */
1.311 brouard 6598: for (i=1; i<=imx; i++) { /* Loop on individuals: reads the data file to get the maximum value of the modality of this covariate Vj*/
1.335 brouard 6599: if(Tvar[k]<=0 || Tvar[k]>=NCOVMAX){
6600: printf("Error k=%d \n",k);
6601: exit(1);
6602: }
1.311 brouard 6603: if(isnan(covar[Tvar[k]][i])){
6604: printf("ERROR, IMaCh doesn't treat fixed quantitative covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6605: fprintf(ficlog,"ERROR, currently IMaCh doesn't treat covariate with missing values V%d=., individual %d will be skipped.\n",Tvar[k],i);
6606: fflush(ficlog);
6607: exit(1);
6608: }
6609: }
1.335 brouard 6610: } /* end Quanti */
1.287 brouard 6611: } /* end of loop on model-covariate k. nbcode[Tvark][1]=-1, nbcode[Tvark][1]=0 and nbcode[Tvark][2]=1 sets the value of covariate k*/
1.242 brouard 6612:
6613: for (k=-1; k< maxncov; k++) Ndum[k]=0;
6614: /* Look at fixed dummy (single or product) covariates to check empty modalities */
6615: for (i=1; i<=ncovmodel-2-nagesqr; i++) { /* -2, cste and age and eventually age*age */
6616: /* Listing of all covariables in statement model to see if some covariates appear twice. For example, V1 appears twice in V1+V1*V2.*/
6617: ij=Tvar[i]; /* Tvar 5,4,3,6,5,7,1,4 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V4*age */
6618: Ndum[ij]++; /* Count the # of 1, 2 etc: {1,1,1,2,2,1,1} because V1 once, V2 once, two V4 and V5 in above */
6619: /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, {2, 1, 1, 1, 2, 1, 1, 0, 0} */
6620: } /* V4+V3+V5, Ndum[1]@5={0, 0, 1, 1, 1} */
6621:
6622: ij=0;
6623: /* for (i=0; i<= maxncov-1; i++) { /\* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) *\/ */
1.335 brouard 6624: for (k=1; k<= cptcovt; k++) { /* cptcovt: total number of covariates of the model (2) nbocc(+)+1 = 8 excepting constant and age and age*age */
6625: /* modmaxcovj is unknown here. Only Ndum[2(V2),3(age*V3), 5(V3*V2) 6(V1*V4) */
1.242 brouard 6626: /*printf("Ndum[%d]=%d\n",i, Ndum[i]);*/
6627: /* if((Ndum[i]!=0) && (i<=ncovcol)){ /\* Tvar[i] <= ncovmodel ? *\/ */
1.335 brouard 6628: if(Ndum[Tvar[k]]!=0 && Dummy[k] == 0 && Typevar[k]==0){ /* Only Dummy simple and non empty in the model */
6629: /* Typevar[k] =0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
6630: /* Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product*/
1.242 brouard 6631: /* If product not in single variable we don't print results */
6632: /*printf("diff Ndum[%d]=%d\n",i, Ndum[i]);*/
1.335 brouard 6633: ++ij;/* V5 + V4 + V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V1, *//* V5 quanti, V2 quanti, V4, V3, V1 dummies */
6634: /* k= 1 2 3 4 5 6 7 8 9 */
6635: /* Tvar[k]= 5 4 3 6 5 2 7 1 1 */
6636: /* ij 1 2 3 */
6637: /* Tvaraff[ij]= 4 3 1 */
6638: /* Tmodelind[ij]=2 3 9 */
6639: /* TmodelInvind[ij]=2 1 1 */
1.242 brouard 6640: Tvaraff[ij]=Tvar[k]; /* For printing combination *//* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, Tvar {5, 4, 3, 6, 5, 2, 7, 1, 1} Tvaraff={4, 3, 1} V4, V3, V1*/
6641: Tmodelind[ij]=k; /* Tmodelind: index in model of dummies Tmodelind[1]=2 V4: pos=2; V3: pos=3, V1=9 {2, 3, 9, ?, ?,} */
6642: TmodelInvind[ij]=Tvar[k]- ncovcol-nqv; /* Inverse TmodelInvind[2=V4]=2 second dummy varying cov (V4)4-1-1 {0, 2, 1, } TmodelInvind[3]=1 */
6643: if(Fixed[k]!=0)
6644: anyvaryingduminmodel=1;
6645: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv)){ */
6646: /* Tvaraff[++ij]=-10; /\* Dont'n know how to treat quantitative variables yet *\/ */
6647: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv)){ */
6648: /* Tvaraff[++ij]=i; /\*For printing (unclear) *\/ */
6649: /* }else if((Ndum[i]!=0) && (i<=ncovcol+nqv+ntv+nqtv)){ */
6650: /* Tvaraff[++ij]=-20; /\* Dont'n know how to treat quantitative variables yet *\/ */
6651: }
6652: } /* Tvaraff[1]@5 {3, 4, -20, 0, 0} Very strange */
6653: /* ij--; */
6654: /* cptcoveff=ij; /\*Number of total covariates*\/ */
1.335 brouard 6655: *cptcov=ij; /* cptcov= Number of total real effective simple dummies (fixed or time arying) effective (used as cptcoveff in other functions)
1.242 brouard 6656: * because they can be excluded from the model and real
6657: * if in the model but excluded because missing values, but how to get k from ij?*/
6658: for(j=ij+1; j<= cptcovt; j++){
6659: Tvaraff[j]=0;
6660: Tmodelind[j]=0;
6661: }
6662: for(j=ntveff+1; j<= cptcovt; j++){
6663: TmodelInvind[j]=0;
6664: }
6665: /* To be sorted */
6666: ;
6667: }
1.126 brouard 6668:
1.145 brouard 6669:
1.126 brouard 6670: /*********** Health Expectancies ****************/
6671:
1.235 brouard 6672: void evsij(double ***eij, double x[], int nlstate, int stepm, int bage, int fage, double **oldm, double **savm, int cij, int estepm,char strstart[], int nres )
1.126 brouard 6673:
6674: {
6675: /* Health expectancies, no variances */
1.329 brouard 6676: /* cij is the combination in the list of combination of dummy covariates */
6677: /* strstart is a string of time at start of computing */
1.164 brouard 6678: int i, j, nhstepm, hstepm, h, nstepm;
1.126 brouard 6679: int nhstepma, nstepma; /* Decreasing with age */
6680: double age, agelim, hf;
6681: double ***p3mat;
6682: double eip;
6683:
1.238 brouard 6684: /* pstamp(ficreseij); */
1.126 brouard 6685: fprintf(ficreseij,"# (a) Life expectancies by health status at initial age and (b) health expectancies by health status at initial age\n");
6686: fprintf(ficreseij,"# Age");
6687: for(i=1; i<=nlstate;i++){
6688: for(j=1; j<=nlstate;j++){
6689: fprintf(ficreseij," e%1d%1d ",i,j);
6690: }
6691: fprintf(ficreseij," e%1d. ",i);
6692: }
6693: fprintf(ficreseij,"\n");
6694:
6695:
6696: if(estepm < stepm){
6697: printf ("Problem %d lower than %d\n",estepm, stepm);
6698: }
6699: else hstepm=estepm;
6700: /* We compute the life expectancy from trapezoids spaced every estepm months
6701: * This is mainly to measure the difference between two models: for example
6702: * if stepm=24 months pijx are given only every 2 years and by summing them
6703: * we are calculating an estimate of the Life Expectancy assuming a linear
6704: * progression in between and thus overestimating or underestimating according
6705: * to the curvature of the survival function. If, for the same date, we
6706: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6707: * to compare the new estimate of Life expectancy with the same linear
6708: * hypothesis. A more precise result, taking into account a more precise
6709: * curvature will be obtained if estepm is as small as stepm. */
6710:
6711: /* For example we decided to compute the life expectancy with the smallest unit */
6712: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6713: nhstepm is the number of hstepm from age to agelim
6714: nstepm is the number of stepm from age to agelin.
1.270 brouard 6715: Look at hpijx to understand the reason which relies in memory size consideration
1.126 brouard 6716: and note for a fixed period like estepm months */
6717: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6718: survival function given by stepm (the optimization length). Unfortunately it
6719: means that if the survival funtion is printed only each two years of age and if
6720: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6721: results. So we changed our mind and took the option of the best precision.
6722: */
6723: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6724:
6725: agelim=AGESUP;
6726: /* If stepm=6 months */
6727: /* Computed by stepm unit matrices, product of hstepm matrices, stored
6728: in an array of nhstepm length: nhstepm=10, hstepm=4, stepm=6 months */
6729:
6730: /* nhstepm age range expressed in number of stepm */
6731: nstepm=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6732: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6733: /* if (stepm >= YEARM) hstepm=1;*/
6734: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6735: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6736:
6737: for (age=bage; age<=fage; age ++){
6738: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6739: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6740: /* if (stepm >= YEARM) hstepm=1;*/
6741: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
6742:
6743: /* If stepm=6 months */
6744: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6745: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
1.330 brouard 6746: /* printf("HELLO evsij Entering hpxij age=%d cij=%d hstepm=%d x[1]=%f nres=%d\n",(int) age, cij, hstepm, x[1], nres); */
1.235 brouard 6747: hpxij(p3mat,nhstepma,age,hstepm,x,nlstate,stepm,oldm, savm, cij, nres);
1.126 brouard 6748:
6749: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
6750:
6751: printf("%d|",(int)age);fflush(stdout);
6752: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6753:
6754: /* Computing expectancies */
6755: for(i=1; i<=nlstate;i++)
6756: for(j=1; j<=nlstate;j++)
6757: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6758: eij[i][j][(int)age] += (p3mat[i][j][h]+p3mat[i][j][h+1])/2.0*hf;
6759:
6760: /* if((int)age==70)printf("i=%2d,j=%2d,h=%2d,age=%3d,%9.4f,%9.4f,%9.4f\n",i,j,h,(int)age,p3mat[i][j][h],hf,eij[i][j][(int)age]);*/
6761:
6762: }
6763:
6764: fprintf(ficreseij,"%3.0f",age );
6765: for(i=1; i<=nlstate;i++){
6766: eip=0;
6767: for(j=1; j<=nlstate;j++){
6768: eip +=eij[i][j][(int)age];
6769: fprintf(ficreseij,"%9.4f", eij[i][j][(int)age] );
6770: }
6771: fprintf(ficreseij,"%9.4f", eip );
6772: }
6773: fprintf(ficreseij,"\n");
6774:
6775: }
6776: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6777: printf("\n");
6778: fprintf(ficlog,"\n");
6779:
6780: }
6781:
1.235 brouard 6782: void cvevsij(double ***eij, double x[], int nlstate, int stepm, int bage, int fage, double **oldm, double **savm, int cij, int estepm,double delti[],double **matcov,char strstart[], int nres )
1.126 brouard 6783:
6784: {
6785: /* Covariances of health expectancies eij and of total life expectancies according
1.222 brouard 6786: to initial status i, ei. .
1.126 brouard 6787: */
1.336 brouard 6788: /* Very time consuming function, but already optimized with precov */
1.126 brouard 6789: int i, j, nhstepm, hstepm, h, nstepm, k, cptj, cptj2, i2, j2, ij, ji;
6790: int nhstepma, nstepma; /* Decreasing with age */
6791: double age, agelim, hf;
6792: double ***p3matp, ***p3matm, ***varhe;
6793: double **dnewm,**doldm;
6794: double *xp, *xm;
6795: double **gp, **gm;
6796: double ***gradg, ***trgradg;
6797: int theta;
6798:
6799: double eip, vip;
6800:
6801: varhe=ma3x(1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int) fage);
6802: xp=vector(1,npar);
6803: xm=vector(1,npar);
6804: dnewm=matrix(1,nlstate*nlstate,1,npar);
6805: doldm=matrix(1,nlstate*nlstate,1,nlstate*nlstate);
6806:
6807: pstamp(ficresstdeij);
6808: fprintf(ficresstdeij,"# Health expectancies with standard errors\n");
6809: fprintf(ficresstdeij,"# Age");
6810: for(i=1; i<=nlstate;i++){
6811: for(j=1; j<=nlstate;j++)
6812: fprintf(ficresstdeij," e%1d%1d (SE)",i,j);
6813: fprintf(ficresstdeij," e%1d. ",i);
6814: }
6815: fprintf(ficresstdeij,"\n");
6816:
6817: pstamp(ficrescveij);
6818: fprintf(ficrescveij,"# Subdiagonal matrix of covariances of health expectancies by age: cov(eij,ekl)\n");
6819: fprintf(ficrescveij,"# Age");
6820: for(i=1; i<=nlstate;i++)
6821: for(j=1; j<=nlstate;j++){
6822: cptj= (j-1)*nlstate+i;
6823: for(i2=1; i2<=nlstate;i2++)
6824: for(j2=1; j2<=nlstate;j2++){
6825: cptj2= (j2-1)*nlstate+i2;
6826: if(cptj2 <= cptj)
6827: fprintf(ficrescveij," %1d%1d,%1d%1d",i,j,i2,j2);
6828: }
6829: }
6830: fprintf(ficrescveij,"\n");
6831:
6832: if(estepm < stepm){
6833: printf ("Problem %d lower than %d\n",estepm, stepm);
6834: }
6835: else hstepm=estepm;
6836: /* We compute the life expectancy from trapezoids spaced every estepm months
6837: * This is mainly to measure the difference between two models: for example
6838: * if stepm=24 months pijx are given only every 2 years and by summing them
6839: * we are calculating an estimate of the Life Expectancy assuming a linear
6840: * progression in between and thus overestimating or underestimating according
6841: * to the curvature of the survival function. If, for the same date, we
6842: * estimate the model with stepm=1 month, we can keep estepm to 24 months
6843: * to compare the new estimate of Life expectancy with the same linear
6844: * hypothesis. A more precise result, taking into account a more precise
6845: * curvature will be obtained if estepm is as small as stepm. */
6846:
6847: /* For example we decided to compute the life expectancy with the smallest unit */
6848: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
6849: nhstepm is the number of hstepm from age to agelim
6850: nstepm is the number of stepm from age to agelin.
6851: Look at hpijx to understand the reason of that which relies in memory size
6852: and note for a fixed period like estepm months */
6853: /* We decided (b) to get a life expectancy respecting the most precise curvature of the
6854: survival function given by stepm (the optimization length). Unfortunately it
6855: means that if the survival funtion is printed only each two years of age and if
6856: you sum them up and add 1 year (area under the trapezoids) you won't get the same
6857: results. So we changed our mind and took the option of the best precision.
6858: */
6859: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
6860:
6861: /* If stepm=6 months */
6862: /* nhstepm age range expressed in number of stepm */
6863: agelim=AGESUP;
6864: nstepm=(int) rint((agelim-bage)*YEARM/stepm);
6865: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6866: /* if (stepm >= YEARM) hstepm=1;*/
6867: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
6868:
6869: p3matp=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6870: p3matm=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6871: gradg=ma3x(0,nhstepm,1,npar,1,nlstate*nlstate);
6872: trgradg =ma3x(0,nhstepm,1,nlstate*nlstate,1,npar);
6873: gp=matrix(0,nhstepm,1,nlstate*nlstate);
6874: gm=matrix(0,nhstepm,1,nlstate*nlstate);
6875:
6876: for (age=bage; age<=fage; age ++){
6877: nstepma=(int) rint((agelim-bage)*YEARM/stepm); /* Biggest nstepm */
6878: /* Typically if 20 years nstepm = 20*12/6=40 stepm */
6879: /* if (stepm >= YEARM) hstepm=1;*/
6880: nhstepma = nstepma/hstepm;/* Expressed in hstepm, typically nhstepma=40/4=10 */
1.218 brouard 6881:
1.126 brouard 6882: /* If stepm=6 months */
6883: /* Computed by stepm unit matrices, product of hstepma matrices, stored
6884: in an array of nhstepma length: nhstepma=10, hstepm=4, stepm=6 months */
6885:
6886: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
1.218 brouard 6887:
1.126 brouard 6888: /* Computing Variances of health expectancies */
6889: /* Gradient is computed with plus gp and minus gm. Code is duplicated in order to
6890: decrease memory allocation */
6891: for(theta=1; theta <=npar; theta++){
6892: for(i=1; i<=npar; i++){
1.222 brouard 6893: xp[i] = x[i] + (i==theta ?delti[theta]:0);
6894: xm[i] = x[i] - (i==theta ?delti[theta]:0);
1.126 brouard 6895: }
1.235 brouard 6896: hpxij(p3matp,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, cij, nres);
6897: hpxij(p3matm,nhstepm,age,hstepm,xm,nlstate,stepm,oldm,savm, cij, nres);
1.218 brouard 6898:
1.126 brouard 6899: for(j=1; j<= nlstate; j++){
1.222 brouard 6900: for(i=1; i<=nlstate; i++){
6901: for(h=0; h<=nhstepm-1; h++){
6902: gp[h][(j-1)*nlstate + i] = (p3matp[i][j][h]+p3matp[i][j][h+1])/2.;
6903: gm[h][(j-1)*nlstate + i] = (p3matm[i][j][h]+p3matm[i][j][h+1])/2.;
6904: }
6905: }
1.126 brouard 6906: }
1.218 brouard 6907:
1.126 brouard 6908: for(ij=1; ij<= nlstate*nlstate; ij++)
1.222 brouard 6909: for(h=0; h<=nhstepm-1; h++){
6910: gradg[h][theta][ij]= (gp[h][ij]-gm[h][ij])/2./delti[theta];
6911: }
1.126 brouard 6912: }/* End theta */
6913:
6914:
6915: for(h=0; h<=nhstepm-1; h++)
6916: for(j=1; j<=nlstate*nlstate;j++)
1.222 brouard 6917: for(theta=1; theta <=npar; theta++)
6918: trgradg[h][j][theta]=gradg[h][theta][j];
1.126 brouard 6919:
1.218 brouard 6920:
1.222 brouard 6921: for(ij=1;ij<=nlstate*nlstate;ij++)
1.126 brouard 6922: for(ji=1;ji<=nlstate*nlstate;ji++)
1.222 brouard 6923: varhe[ij][ji][(int)age] =0.;
1.218 brouard 6924:
1.222 brouard 6925: printf("%d|",(int)age);fflush(stdout);
6926: fprintf(ficlog,"%d|",(int)age);fflush(ficlog);
6927: for(h=0;h<=nhstepm-1;h++){
1.126 brouard 6928: for(k=0;k<=nhstepm-1;k++){
1.222 brouard 6929: matprod2(dnewm,trgradg[h],1,nlstate*nlstate,1,npar,1,npar,matcov);
6930: matprod2(doldm,dnewm,1,nlstate*nlstate,1,npar,1,nlstate*nlstate,gradg[k]);
6931: for(ij=1;ij<=nlstate*nlstate;ij++)
6932: for(ji=1;ji<=nlstate*nlstate;ji++)
6933: varhe[ij][ji][(int)age] += doldm[ij][ji]*hf*hf;
1.126 brouard 6934: }
6935: }
1.320 brouard 6936: /* if((int)age ==50){ */
6937: /* printf(" age=%d cij=%d nres=%d varhe[%d][%d]=%f ",(int)age, cij, nres, 1,2,varhe[1][2]); */
6938: /* } */
1.126 brouard 6939: /* Computing expectancies */
1.235 brouard 6940: hpxij(p3matm,nhstepm,age,hstepm,x,nlstate,stepm,oldm, savm, cij,nres);
1.126 brouard 6941: for(i=1; i<=nlstate;i++)
6942: for(j=1; j<=nlstate;j++)
1.222 brouard 6943: for (h=0, eij[i][j][(int)age]=0; h<=nhstepm-1; h++){
6944: eij[i][j][(int)age] += (p3matm[i][j][h]+p3matm[i][j][h+1])/2.0*hf;
1.218 brouard 6945:
1.222 brouard 6946: /* if((int)age==70)printf("i=%2d,j=%2d,h=%2d,age=%3d,%9.4f,%9.4f,%9.4f\n",i,j,h,(int)age,p3mat[i][j][h],hf,eij[i][j][(int)age]);*/
1.218 brouard 6947:
1.222 brouard 6948: }
1.269 brouard 6949:
6950: /* Standard deviation of expectancies ij */
1.126 brouard 6951: fprintf(ficresstdeij,"%3.0f",age );
6952: for(i=1; i<=nlstate;i++){
6953: eip=0.;
6954: vip=0.;
6955: for(j=1; j<=nlstate;j++){
1.222 brouard 6956: eip += eij[i][j][(int)age];
6957: for(k=1; k<=nlstate;k++) /* Sum on j and k of cov(eij,eik) */
6958: vip += varhe[(j-1)*nlstate+i][(k-1)*nlstate+i][(int)age];
6959: fprintf(ficresstdeij," %9.4f (%.4f)", eij[i][j][(int)age], sqrt(varhe[(j-1)*nlstate+i][(j-1)*nlstate+i][(int)age]) );
1.126 brouard 6960: }
6961: fprintf(ficresstdeij," %9.4f (%.4f)", eip, sqrt(vip));
6962: }
6963: fprintf(ficresstdeij,"\n");
1.218 brouard 6964:
1.269 brouard 6965: /* Variance of expectancies ij */
1.126 brouard 6966: fprintf(ficrescveij,"%3.0f",age );
6967: for(i=1; i<=nlstate;i++)
6968: for(j=1; j<=nlstate;j++){
1.222 brouard 6969: cptj= (j-1)*nlstate+i;
6970: for(i2=1; i2<=nlstate;i2++)
6971: for(j2=1; j2<=nlstate;j2++){
6972: cptj2= (j2-1)*nlstate+i2;
6973: if(cptj2 <= cptj)
6974: fprintf(ficrescveij," %.4f", varhe[cptj][cptj2][(int)age]);
6975: }
1.126 brouard 6976: }
6977: fprintf(ficrescveij,"\n");
1.218 brouard 6978:
1.126 brouard 6979: }
6980: free_matrix(gm,0,nhstepm,1,nlstate*nlstate);
6981: free_matrix(gp,0,nhstepm,1,nlstate*nlstate);
6982: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate*nlstate);
6983: free_ma3x(trgradg,0,nhstepm,1,nlstate*nlstate,1,npar);
6984: free_ma3x(p3matm,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6985: free_ma3x(p3matp,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
6986: printf("\n");
6987: fprintf(ficlog,"\n");
1.218 brouard 6988:
1.126 brouard 6989: free_vector(xm,1,npar);
6990: free_vector(xp,1,npar);
6991: free_matrix(dnewm,1,nlstate*nlstate,1,npar);
6992: free_matrix(doldm,1,nlstate*nlstate,1,nlstate*nlstate);
6993: free_ma3x(varhe,1,nlstate*nlstate,1,nlstate*nlstate,(int) bage, (int)fage);
6994: }
1.218 brouard 6995:
1.126 brouard 6996: /************ Variance ******************/
1.235 brouard 6997: void varevsij(char optionfilefiname[], double ***vareij, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **prlim, double ftolpl, int *ncvyearp, int ij, int estepm, int cptcov, int cptcod, int popbased, int mobilav, char strstart[], int nres)
1.218 brouard 6998: {
1.279 brouard 6999: /** Variance of health expectancies
7000: * double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double ** savm,double ftolpl);
7001: * double **newm;
7002: * int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav)
7003: */
1.218 brouard 7004:
7005: /* int movingaverage(); */
7006: double **dnewm,**doldm;
7007: double **dnewmp,**doldmp;
7008: int i, j, nhstepm, hstepm, h, nstepm ;
1.288 brouard 7009: int first=0;
1.218 brouard 7010: int k;
7011: double *xp;
1.279 brouard 7012: double **gp, **gm; /**< for var eij */
7013: double ***gradg, ***trgradg; /**< for var eij */
7014: double **gradgp, **trgradgp; /**< for var p point j */
7015: double *gpp, *gmp; /**< for var p point j */
7016: double **varppt; /**< for var p point j nlstate to nlstate+ndeath */
1.218 brouard 7017: double ***p3mat;
7018: double age,agelim, hf;
7019: /* double ***mobaverage; */
7020: int theta;
7021: char digit[4];
7022: char digitp[25];
7023:
7024: char fileresprobmorprev[FILENAMELENGTH];
7025:
7026: if(popbased==1){
7027: if(mobilav!=0)
7028: strcpy(digitp,"-POPULBASED-MOBILAV_");
7029: else strcpy(digitp,"-POPULBASED-NOMOBIL_");
7030: }
7031: else
7032: strcpy(digitp,"-STABLBASED_");
1.126 brouard 7033:
1.218 brouard 7034: /* if (mobilav!=0) { */
7035: /* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7036: /* if (movingaverage(probs, bage, fage, mobaverage,mobilav)!=0){ */
7037: /* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); */
7038: /* printf(" Error in movingaverage mobilav=%d\n",mobilav); */
7039: /* } */
7040: /* } */
7041:
7042: strcpy(fileresprobmorprev,"PRMORPREV-");
7043: sprintf(digit,"%-d",ij);
7044: /*printf("DIGIT=%s, ij=%d ijr=%-d|\n",digit, ij,ij);*/
7045: strcat(fileresprobmorprev,digit); /* Tvar to be done */
7046: strcat(fileresprobmorprev,digitp); /* Popbased or not, mobilav or not */
7047: strcat(fileresprobmorprev,fileresu);
7048: if((ficresprobmorprev=fopen(fileresprobmorprev,"w"))==NULL) {
7049: printf("Problem with resultfile: %s\n", fileresprobmorprev);
7050: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobmorprev);
7051: }
7052: printf("Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7053: fprintf(ficlog,"Computing total mortality p.j=w1*p1j+w2*p2j+..: result on file '%s' \n",fileresprobmorprev);
7054: pstamp(ficresprobmorprev);
7055: fprintf(ficresprobmorprev,"# probabilities of dying before estepm=%d months for people of exact age and weighted probabilities w1*p1j+w2*p2j+... stand dev in()\n",estepm);
1.238 brouard 7056: fprintf(ficresprobmorprev,"# Selected quantitative variables and dummies");
1.337 brouard 7057:
7058: /* We use TinvDoQresult[nres][resultmodel[nres][j] we sort according to the equation model and the resultline: it is a choice */
7059: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ /\* To be done*\/ */
7060: /* fprintf(ficresprobmorprev," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
7061: /* } */
7062: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */ /* To be done*/
1.344 brouard 7063: /* fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); */
1.337 brouard 7064: fprintf(ficresprobmorprev," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 7065: }
1.337 brouard 7066: /* for(j=1;j<=cptcoveff;j++) */
7067: /* fprintf(ficresprobmorprev," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(ij,TnsdVar[Tvaraff[j]])]); */
1.238 brouard 7068: fprintf(ficresprobmorprev,"\n");
7069:
1.218 brouard 7070: fprintf(ficresprobmorprev,"# Age cov=%-d",ij);
7071: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7072: fprintf(ficresprobmorprev," p.%-d SE",j);
7073: for(i=1; i<=nlstate;i++)
7074: fprintf(ficresprobmorprev," w%1d p%-d%-d",i,i,j);
7075: }
7076: fprintf(ficresprobmorprev,"\n");
7077:
7078: fprintf(ficgp,"\n# Routine varevsij");
7079: fprintf(ficgp,"\nunset title \n");
7080: /* fprintf(fichtm, "#Local time at start: %s", strstart);*/
7081: fprintf(fichtm,"\n<li><h4> Computing probabilities of dying over estepm months as a weighted average (i.e global mortality independent of initial healh state)</h4></li>\n");
7082: fprintf(fichtm,"\n<br>%s <br>\n",digitp);
1.279 brouard 7083:
1.218 brouard 7084: varppt = matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7085: pstamp(ficresvij);
7086: fprintf(ficresvij,"# Variance and covariance of health expectancies e.j \n# (weighted average of eij where weights are ");
7087: if(popbased==1)
7088: fprintf(ficresvij,"the age specific prevalence observed (cross-sectionally) in the population i.e cross-sectionally\n in each health state (popbased=1) (mobilav=%d\n",mobilav);
7089: else
7090: fprintf(ficresvij,"the age specific period (stable) prevalences in each health state \n");
7091: fprintf(ficresvij,"# Age");
7092: for(i=1; i<=nlstate;i++)
7093: for(j=1; j<=nlstate;j++)
7094: fprintf(ficresvij," Cov(e.%1d, e.%1d)",i,j);
7095: fprintf(ficresvij,"\n");
7096:
7097: xp=vector(1,npar);
7098: dnewm=matrix(1,nlstate,1,npar);
7099: doldm=matrix(1,nlstate,1,nlstate);
7100: dnewmp= matrix(nlstate+1,nlstate+ndeath,1,npar);
7101: doldmp= matrix(nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7102:
7103: gradgp=matrix(1,npar,nlstate+1,nlstate+ndeath);
7104: gpp=vector(nlstate+1,nlstate+ndeath);
7105: gmp=vector(nlstate+1,nlstate+ndeath);
7106: trgradgp =matrix(nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
1.126 brouard 7107:
1.218 brouard 7108: if(estepm < stepm){
7109: printf ("Problem %d lower than %d\n",estepm, stepm);
7110: }
7111: else hstepm=estepm;
7112: /* For example we decided to compute the life expectancy with the smallest unit */
7113: /* hstepm beeing the number of stepms, if hstepm=1 the length of hstepm is stepm.
7114: nhstepm is the number of hstepm from age to agelim
7115: nstepm is the number of stepm from age to agelim.
7116: Look at function hpijx to understand why because of memory size limitations,
7117: we decided (b) to get a life expectancy respecting the most precise curvature of the
7118: survival function given by stepm (the optimization length). Unfortunately it
7119: means that if the survival funtion is printed every two years of age and if
7120: you sum them up and add 1 year (area under the trapezoids) you won't get the same
7121: results. So we changed our mind and took the option of the best precision.
7122: */
7123: hstepm=hstepm/stepm; /* Typically in stepm units, if stepm=6 & estepm=24 , = 24/6 months = 4 */
7124: agelim = AGESUP;
7125: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7126: nstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7127: nhstepm = nstepm/hstepm;/* Expressed in hstepm, typically nhstepm=40/4=10 */
7128: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7129: gradg=ma3x(0,nhstepm,1,npar,1,nlstate);
7130: gp=matrix(0,nhstepm,1,nlstate);
7131: gm=matrix(0,nhstepm,1,nlstate);
7132:
7133:
7134: for(theta=1; theta <=npar; theta++){
7135: for(i=1; i<=npar; i++){ /* Computes gradient x + delta*/
7136: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7137: }
1.279 brouard 7138: /**< Computes the prevalence limit with parameter theta shifted of delta up to ftolpl precision and
7139: * returns into prlim .
1.288 brouard 7140: */
1.242 brouard 7141: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.279 brouard 7142:
7143: /* If popbased = 1 we use crossection prevalences. Previous step is useless but prlim is created */
1.218 brouard 7144: if (popbased==1) {
7145: if(mobilav ==0){
7146: for(i=1; i<=nlstate;i++)
7147: prlim[i][i]=probs[(int)age][i][ij];
7148: }else{ /* mobilav */
7149: for(i=1; i<=nlstate;i++)
7150: prlim[i][i]=mobaverage[(int)age][i][ij];
7151: }
7152: }
1.295 brouard 7153: /**< Computes the shifted transition matrix \f$ {}{h}_p^{ij}x\f$ at horizon h.
1.279 brouard 7154: */
7155: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres); /* Returns p3mat[i][j][h] for h=0 to nhstepm */
1.292 brouard 7156: /**< And for each alive state j, sums over i \f$ w^i_x {}{h}_p^{ij}x\f$, which are the probability
1.279 brouard 7157: * at horizon h in state j including mortality.
7158: */
1.218 brouard 7159: for(j=1; j<= nlstate; j++){
7160: for(h=0; h<=nhstepm; h++){
7161: for(i=1, gp[h][j]=0.;i<=nlstate;i++)
7162: gp[h][j] += prlim[i][i]*p3mat[i][j][h];
7163: }
7164: }
1.279 brouard 7165: /* Next for computing shifted+ probability of death (h=1 means
1.218 brouard 7166: computed over hstepm matrices product = hstepm*stepm months)
1.279 brouard 7167: as a weighted average of prlim(i) * p(i,j) p.3=w1*p13 + w2*p23 .
1.218 brouard 7168: */
7169: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7170: for(i=1,gpp[j]=0.; i<= nlstate; i++)
7171: gpp[j] += prlim[i][i]*p3mat[i][j][1];
1.279 brouard 7172: }
7173:
7174: /* Again with minus shift */
1.218 brouard 7175:
7176: for(i=1; i<=npar; i++) /* Computes gradient x - delta */
7177: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7178:
1.242 brouard 7179: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp, ij, nres);
1.218 brouard 7180:
7181: if (popbased==1) {
7182: if(mobilav ==0){
7183: for(i=1; i<=nlstate;i++)
7184: prlim[i][i]=probs[(int)age][i][ij];
7185: }else{ /* mobilav */
7186: for(i=1; i<=nlstate;i++)
7187: prlim[i][i]=mobaverage[(int)age][i][ij];
7188: }
7189: }
7190:
1.235 brouard 7191: hpxij(p3mat,nhstepm,age,hstepm,xp,nlstate,stepm,oldm,savm, ij,nres);
1.218 brouard 7192:
7193: for(j=1; j<= nlstate; j++){ /* Sum of wi * eij = e.j */
7194: for(h=0; h<=nhstepm; h++){
7195: for(i=1, gm[h][j]=0.;i<=nlstate;i++)
7196: gm[h][j] += prlim[i][i]*p3mat[i][j][h];
7197: }
7198: }
7199: /* This for computing probability of death (h=1 means
7200: computed over hstepm matrices product = hstepm*stepm months)
7201: as a weighted average of prlim.
7202: */
7203: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7204: for(i=1,gmp[j]=0.; i<= nlstate; i++)
7205: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7206: }
1.279 brouard 7207: /* end shifting computations */
7208:
7209: /**< Computing gradient matrix at horizon h
7210: */
1.218 brouard 7211: for(j=1; j<= nlstate; j++) /* vareij */
7212: for(h=0; h<=nhstepm; h++){
7213: gradg[h][theta][j]= (gp[h][j]-gm[h][j])/2./delti[theta];
7214: }
1.279 brouard 7215: /**< Gradient of overall mortality p.3 (or p.j)
7216: */
7217: for(j=nlstate+1; j<= nlstate+ndeath; j++){ /* var mu mortality from j */
1.218 brouard 7218: gradgp[theta][j]= (gpp[j]-gmp[j])/2./delti[theta];
7219: }
7220:
7221: } /* End theta */
1.279 brouard 7222:
7223: /* We got the gradient matrix for each theta and state j */
1.218 brouard 7224: trgradg =ma3x(0,nhstepm,1,nlstate,1,npar); /* veij */
7225:
7226: for(h=0; h<=nhstepm; h++) /* veij */
7227: for(j=1; j<=nlstate;j++)
7228: for(theta=1; theta <=npar; theta++)
7229: trgradg[h][j][theta]=gradg[h][theta][j];
7230:
7231: for(j=nlstate+1; j<=nlstate+ndeath;j++) /* mu */
7232: for(theta=1; theta <=npar; theta++)
7233: trgradgp[j][theta]=gradgp[theta][j];
1.279 brouard 7234: /**< as well as its transposed matrix
7235: */
1.218 brouard 7236:
7237: hf=hstepm*stepm/YEARM; /* Duration of hstepm expressed in year unit. */
7238: for(i=1;i<=nlstate;i++)
7239: for(j=1;j<=nlstate;j++)
7240: vareij[i][j][(int)age] =0.;
1.279 brouard 7241:
7242: /* Computing trgradg by matcov by gradg at age and summing over h
7243: * and k (nhstepm) formula 15 of article
7244: * Lievre-Brouard-Heathcote
7245: */
7246:
1.218 brouard 7247: for(h=0;h<=nhstepm;h++){
7248: for(k=0;k<=nhstepm;k++){
7249: matprod2(dnewm,trgradg[h],1,nlstate,1,npar,1,npar,matcov);
7250: matprod2(doldm,dnewm,1,nlstate,1,npar,1,nlstate,gradg[k]);
7251: for(i=1;i<=nlstate;i++)
7252: for(j=1;j<=nlstate;j++)
7253: vareij[i][j][(int)age] += doldm[i][j]*hf*hf;
7254: }
7255: }
7256:
1.279 brouard 7257: /* pptj is p.3 or p.j = trgradgp by cov by gradgp, variance of
7258: * p.j overall mortality formula 49 but computed directly because
7259: * we compute the grad (wix pijx) instead of grad (pijx),even if
7260: * wix is independent of theta.
7261: */
1.218 brouard 7262: matprod2(dnewmp,trgradgp,nlstate+1,nlstate+ndeath,1,npar,1,npar,matcov);
7263: matprod2(doldmp,dnewmp,nlstate+1,nlstate+ndeath,1,npar,nlstate+1,nlstate+ndeath,gradgp);
7264: for(j=nlstate+1;j<=nlstate+ndeath;j++)
7265: for(i=nlstate+1;i<=nlstate+ndeath;i++)
7266: varppt[j][i]=doldmp[j][i];
7267: /* end ppptj */
7268: /* x centered again */
7269:
1.242 brouard 7270: prevalim(prlim,nlstate,x,age,oldm,savm,ftolpl,ncvyearp,ij, nres);
1.218 brouard 7271:
7272: if (popbased==1) {
7273: if(mobilav ==0){
7274: for(i=1; i<=nlstate;i++)
7275: prlim[i][i]=probs[(int)age][i][ij];
7276: }else{ /* mobilav */
7277: for(i=1; i<=nlstate;i++)
7278: prlim[i][i]=mobaverage[(int)age][i][ij];
7279: }
7280: }
7281:
7282: /* This for computing probability of death (h=1 means
7283: computed over hstepm (estepm) matrices product = hstepm*stepm months)
7284: as a weighted average of prlim.
7285: */
1.235 brouard 7286: hpxij(p3mat,nhstepm,age,hstepm,x,nlstate,stepm,oldm,savm, ij, nres);
1.218 brouard 7287: for(j=nlstate+1;j<=nlstate+ndeath;j++){
7288: for(i=1,gmp[j]=0.;i<= nlstate; i++)
7289: gmp[j] += prlim[i][i]*p3mat[i][j][1];
7290: }
7291: /* end probability of death */
7292:
7293: fprintf(ficresprobmorprev,"%3d %d ",(int) age, ij);
7294: for(j=nlstate+1; j<=(nlstate+ndeath);j++){
7295: fprintf(ficresprobmorprev," %11.3e %11.3e",gmp[j], sqrt(varppt[j][j]));
7296: for(i=1; i<=nlstate;i++){
7297: fprintf(ficresprobmorprev," %11.3e %11.3e ",prlim[i][i],p3mat[i][j][1]);
7298: }
7299: }
7300: fprintf(ficresprobmorprev,"\n");
7301:
7302: fprintf(ficresvij,"%.0f ",age );
7303: for(i=1; i<=nlstate;i++)
7304: for(j=1; j<=nlstate;j++){
7305: fprintf(ficresvij," %.4f", vareij[i][j][(int)age]);
7306: }
7307: fprintf(ficresvij,"\n");
7308: free_matrix(gp,0,nhstepm,1,nlstate);
7309: free_matrix(gm,0,nhstepm,1,nlstate);
7310: free_ma3x(gradg,0,nhstepm,1,npar,1,nlstate);
7311: free_ma3x(trgradg,0,nhstepm,1,nlstate,1,npar);
7312: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
7313: } /* End age */
7314: free_vector(gpp,nlstate+1,nlstate+ndeath);
7315: free_vector(gmp,nlstate+1,nlstate+ndeath);
7316: free_matrix(gradgp,1,npar,nlstate+1,nlstate+ndeath);
7317: free_matrix(trgradgp,nlstate+1,nlstate+ndeath,1,npar); /* mu or p point j*/
7318: /* fprintf(ficgp,"\nunset parametric;unset label; set ter png small size 320, 240"); */
7319: fprintf(ficgp,"\nunset parametric;unset label; set ter svg size 640, 480");
7320: /* for(j=nlstate+1; j<= nlstate+ndeath; j++){ *//* Only the first actually */
7321: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Force of mortality (year-1)\";");
7322: fprintf(ficgp,"\nset out \"%s%s.svg\";",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
7323: /* fprintf(ficgp,"\n plot \"%s\" u 1:($3*%6.3f) not w l 1 ",fileresprobmorprev,YEARM/estepm); */
7324: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)*%6.3f) t \"95\%% interval\" w l 2 ",fileresprobmorprev,YEARM/estepm); */
7325: /* fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)*%6.3f) not w l 2 ",fileresprobmorprev,YEARM/estepm); */
7326: fprintf(ficgp,"\n plot \"%s\" u 1:($3) not w l lt 1 ",subdirf(fileresprobmorprev));
7327: fprintf(ficgp,"\n replot \"%s\" u 1:(($3+1.96*$4)) t \"95%% interval\" w l lt 2 ",subdirf(fileresprobmorprev));
7328: fprintf(ficgp,"\n replot \"%s\" u 1:(($3-1.96*$4)) not w l lt 2 ",subdirf(fileresprobmorprev));
7329: fprintf(fichtm,"\n<br> File (multiple files are possible if covariates are present): <A href=\"%s\">%s</a>\n",subdirf(fileresprobmorprev),subdirf(fileresprobmorprev));
7330: fprintf(fichtm,"\n<br> Probability is computed over estepm=%d months. <br> <img src=\"%s%s.svg\"> <br>\n", estepm,subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
7331: /* fprintf(fichtm,"\n<br> Probability is computed over estepm=%d months and then divided by estepm and multiplied by %.0f in order to have the probability to die over a year <br> <img src=\"varmuptjgr%s%s.svg\"> <br>\n", stepm,YEARM,digitp,digit);
1.126 brouard 7332: */
1.218 brouard 7333: /* fprintf(ficgp,"\nset out \"varmuptjgr%s%s%s.svg\";replot;",digitp,optionfilefiname,digit); */
7334: fprintf(ficgp,"\nset out;\nset out \"%s%s.svg\";replot;set out;\n",subdirf3(optionfilefiname,"VARMUPTJGR-",digitp),digit);
1.126 brouard 7335:
1.218 brouard 7336: free_vector(xp,1,npar);
7337: free_matrix(doldm,1,nlstate,1,nlstate);
7338: free_matrix(dnewm,1,nlstate,1,npar);
7339: free_matrix(doldmp,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7340: free_matrix(dnewmp,nlstate+1,nlstate+ndeath,1,npar);
7341: free_matrix(varppt,nlstate+1,nlstate+ndeath,nlstate+1,nlstate+ndeath);
7342: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
7343: fclose(ficresprobmorprev);
7344: fflush(ficgp);
7345: fflush(fichtm);
7346: } /* end varevsij */
1.126 brouard 7347:
7348: /************ Variance of prevlim ******************/
1.269 brouard 7349: void varprevlim(char fileresvpl[], FILE *ficresvpl, double **varpl, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **prlim, double ftolpl, int *ncvyearp, int ij, char strstart[], int nres)
1.126 brouard 7350: {
1.205 brouard 7351: /* Variance of prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
1.126 brouard 7352: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
1.164 brouard 7353:
1.268 brouard 7354: double **dnewmpar,**doldm;
1.126 brouard 7355: int i, j, nhstepm, hstepm;
7356: double *xp;
7357: double *gp, *gm;
7358: double **gradg, **trgradg;
1.208 brouard 7359: double **mgm, **mgp;
1.126 brouard 7360: double age,agelim;
7361: int theta;
7362:
7363: pstamp(ficresvpl);
1.288 brouard 7364: fprintf(ficresvpl,"# Standard deviation of period (forward stable) prevalences \n");
1.241 brouard 7365: fprintf(ficresvpl,"# Age ");
7366: if(nresult >=1)
7367: fprintf(ficresvpl," Result# ");
1.126 brouard 7368: for(i=1; i<=nlstate;i++)
7369: fprintf(ficresvpl," %1d-%1d",i,i);
7370: fprintf(ficresvpl,"\n");
7371:
7372: xp=vector(1,npar);
1.268 brouard 7373: dnewmpar=matrix(1,nlstate,1,npar);
1.126 brouard 7374: doldm=matrix(1,nlstate,1,nlstate);
7375:
7376: hstepm=1*YEARM; /* Every year of age */
7377: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7378: agelim = AGESUP;
7379: for (age=bage; age<=fage; age ++){ /* If stepm=6 months */
7380: nhstepm=(int) rint((agelim-age)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7381: if (stepm >= YEARM) hstepm=1;
7382: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7383: gradg=matrix(1,npar,1,nlstate);
1.208 brouard 7384: mgp=matrix(1,npar,1,nlstate);
7385: mgm=matrix(1,npar,1,nlstate);
1.126 brouard 7386: gp=vector(1,nlstate);
7387: gm=vector(1,nlstate);
7388:
7389: for(theta=1; theta <=npar; theta++){
7390: for(i=1; i<=npar; i++){ /* Computes gradient */
7391: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7392: }
1.288 brouard 7393: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7394: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7395: /* else */
7396: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7397: for(i=1;i<=nlstate;i++){
1.126 brouard 7398: gp[i] = prlim[i][i];
1.208 brouard 7399: mgp[theta][i] = prlim[i][i];
7400: }
1.126 brouard 7401: for(i=1; i<=npar; i++) /* Computes gradient */
7402: xp[i] = x[i] - (i==theta ?delti[theta]:0);
1.288 brouard 7403: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ) */
7404: /* prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres); */
7405: /* else */
7406: prevalim(prlim,nlstate,xp,age,oldm,savm,ftolpl,ncvyearp,ij,nres);
1.208 brouard 7407: for(i=1;i<=nlstate;i++){
1.126 brouard 7408: gm[i] = prlim[i][i];
1.208 brouard 7409: mgm[theta][i] = prlim[i][i];
7410: }
1.126 brouard 7411: for(i=1;i<=nlstate;i++)
7412: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
1.209 brouard 7413: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
1.126 brouard 7414: } /* End theta */
7415:
7416: trgradg =matrix(1,nlstate,1,npar);
7417:
7418: for(j=1; j<=nlstate;j++)
7419: for(theta=1; theta <=npar; theta++)
7420: trgradg[j][theta]=gradg[theta][j];
1.209 brouard 7421: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7422: /* printf("\nmgm mgp %d ",(int)age); */
7423: /* for(j=1; j<=nlstate;j++){ */
7424: /* printf(" %d ",j); */
7425: /* for(theta=1; theta <=npar; theta++) */
7426: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7427: /* printf("\n "); */
7428: /* } */
7429: /* } */
7430: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7431: /* printf("\n gradg %d ",(int)age); */
7432: /* for(j=1; j<=nlstate;j++){ */
7433: /* printf("%d ",j); */
7434: /* for(theta=1; theta <=npar; theta++) */
7435: /* printf("%d %lf ",theta,gradg[theta][j]); */
7436: /* printf("\n "); */
7437: /* } */
7438: /* } */
1.126 brouard 7439:
7440: for(i=1;i<=nlstate;i++)
7441: varpl[i][(int)age] =0.;
1.209 brouard 7442: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
1.268 brouard 7443: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7444: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7445: }else{
1.268 brouard 7446: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7447: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
1.205 brouard 7448: }
1.126 brouard 7449: for(i=1;i<=nlstate;i++)
7450: varpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7451:
7452: fprintf(ficresvpl,"%.0f ",age );
1.241 brouard 7453: if(nresult >=1)
7454: fprintf(ficresvpl,"%d ",nres );
1.288 brouard 7455: for(i=1; i<=nlstate;i++){
1.126 brouard 7456: fprintf(ficresvpl," %.5f (%.5f)",prlim[i][i],sqrt(varpl[i][(int)age]));
1.288 brouard 7457: /* for(j=1;j<=nlstate;j++) */
7458: /* fprintf(ficresvpl," %d %.5f ",j,prlim[j][i]); */
7459: }
1.126 brouard 7460: fprintf(ficresvpl,"\n");
7461: free_vector(gp,1,nlstate);
7462: free_vector(gm,1,nlstate);
1.208 brouard 7463: free_matrix(mgm,1,npar,1,nlstate);
7464: free_matrix(mgp,1,npar,1,nlstate);
1.126 brouard 7465: free_matrix(gradg,1,npar,1,nlstate);
7466: free_matrix(trgradg,1,nlstate,1,npar);
7467: } /* End age */
7468:
7469: free_vector(xp,1,npar);
7470: free_matrix(doldm,1,nlstate,1,npar);
1.268 brouard 7471: free_matrix(dnewmpar,1,nlstate,1,nlstate);
7472:
7473: }
7474:
7475:
7476: /************ Variance of backprevalence limit ******************/
1.269 brouard 7477: void varbrevlim(char fileresvbl[], FILE *ficresvbl, double **varbpl, double **matcov, double x[], double delti[], int nlstate, int stepm, double bage, double fage, double **oldm, double **savm, double **bprlim, double ftolpl, int mobilavproj, int *ncvyearp, int ij, char strstart[], int nres)
1.268 brouard 7478: {
7479: /* Variance of backward prevalence limit for each state ij using current parameters x[] and estimates of neighbourhood give by delti*/
7480: /* double **prevalim(double **prlim, int nlstate, double *xp, double age, double **oldm, double **savm,double ftolpl);*/
7481:
7482: double **dnewmpar,**doldm;
7483: int i, j, nhstepm, hstepm;
7484: double *xp;
7485: double *gp, *gm;
7486: double **gradg, **trgradg;
7487: double **mgm, **mgp;
7488: double age,agelim;
7489: int theta;
7490:
7491: pstamp(ficresvbl);
7492: fprintf(ficresvbl,"# Standard deviation of back (stable) prevalences \n");
7493: fprintf(ficresvbl,"# Age ");
7494: if(nresult >=1)
7495: fprintf(ficresvbl," Result# ");
7496: for(i=1; i<=nlstate;i++)
7497: fprintf(ficresvbl," %1d-%1d",i,i);
7498: fprintf(ficresvbl,"\n");
7499:
7500: xp=vector(1,npar);
7501: dnewmpar=matrix(1,nlstate,1,npar);
7502: doldm=matrix(1,nlstate,1,nlstate);
7503:
7504: hstepm=1*YEARM; /* Every year of age */
7505: hstepm=hstepm/stepm; /* Typically in stepm units, if j= 2 years, = 2/6 months = 4 */
7506: agelim = AGEINF;
7507: for (age=fage; age>=bage; age --){ /* If stepm=6 months */
7508: nhstepm=(int) rint((age-agelim)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
7509: if (stepm >= YEARM) hstepm=1;
7510: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
7511: gradg=matrix(1,npar,1,nlstate);
7512: mgp=matrix(1,npar,1,nlstate);
7513: mgm=matrix(1,npar,1,nlstate);
7514: gp=vector(1,nlstate);
7515: gm=vector(1,nlstate);
7516:
7517: for(theta=1; theta <=npar; theta++){
7518: for(i=1; i<=npar; i++){ /* Computes gradient */
7519: xp[i] = x[i] + (i==theta ?delti[theta]:0);
7520: }
7521: if(mobilavproj > 0 )
7522: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7523: else
7524: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7525: for(i=1;i<=nlstate;i++){
7526: gp[i] = bprlim[i][i];
7527: mgp[theta][i] = bprlim[i][i];
7528: }
7529: for(i=1; i<=npar; i++) /* Computes gradient */
7530: xp[i] = x[i] - (i==theta ?delti[theta]:0);
7531: if(mobilavproj > 0 )
7532: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7533: else
7534: bprevalim(bprlim, mobaverage,nlstate,xp,age,ftolpl,ncvyearp,ij,nres);
7535: for(i=1;i<=nlstate;i++){
7536: gm[i] = bprlim[i][i];
7537: mgm[theta][i] = bprlim[i][i];
7538: }
7539: for(i=1;i<=nlstate;i++)
7540: gradg[theta][i]= (gp[i]-gm[i])/2./delti[theta];
7541: /* gradg[theta][2]= -gradg[theta][1]; */ /* For testing if nlstate=2 */
7542: } /* End theta */
7543:
7544: trgradg =matrix(1,nlstate,1,npar);
7545:
7546: for(j=1; j<=nlstate;j++)
7547: for(theta=1; theta <=npar; theta++)
7548: trgradg[j][theta]=gradg[theta][j];
7549: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7550: /* printf("\nmgm mgp %d ",(int)age); */
7551: /* for(j=1; j<=nlstate;j++){ */
7552: /* printf(" %d ",j); */
7553: /* for(theta=1; theta <=npar; theta++) */
7554: /* printf(" %d %lf %lf",theta,mgm[theta][j],mgp[theta][j]); */
7555: /* printf("\n "); */
7556: /* } */
7557: /* } */
7558: /* if((int)age==79 ||(int)age== 80 ||(int)age== 81 ){ */
7559: /* printf("\n gradg %d ",(int)age); */
7560: /* for(j=1; j<=nlstate;j++){ */
7561: /* printf("%d ",j); */
7562: /* for(theta=1; theta <=npar; theta++) */
7563: /* printf("%d %lf ",theta,gradg[theta][j]); */
7564: /* printf("\n "); */
7565: /* } */
7566: /* } */
7567:
7568: for(i=1;i<=nlstate;i++)
7569: varbpl[i][(int)age] =0.;
7570: if((int)age==79 ||(int)age== 80 ||(int)age== 81){
7571: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7572: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7573: }else{
7574: matprod2(dnewmpar,trgradg,1,nlstate,1,npar,1,npar,matcov);
7575: matprod2(doldm,dnewmpar,1,nlstate,1,npar,1,nlstate,gradg);
7576: }
7577: for(i=1;i<=nlstate;i++)
7578: varbpl[i][(int)age] = doldm[i][i]; /* Covariances are useless */
7579:
7580: fprintf(ficresvbl,"%.0f ",age );
7581: if(nresult >=1)
7582: fprintf(ficresvbl,"%d ",nres );
7583: for(i=1; i<=nlstate;i++)
7584: fprintf(ficresvbl," %.5f (%.5f)",bprlim[i][i],sqrt(varbpl[i][(int)age]));
7585: fprintf(ficresvbl,"\n");
7586: free_vector(gp,1,nlstate);
7587: free_vector(gm,1,nlstate);
7588: free_matrix(mgm,1,npar,1,nlstate);
7589: free_matrix(mgp,1,npar,1,nlstate);
7590: free_matrix(gradg,1,npar,1,nlstate);
7591: free_matrix(trgradg,1,nlstate,1,npar);
7592: } /* End age */
7593:
7594: free_vector(xp,1,npar);
7595: free_matrix(doldm,1,nlstate,1,npar);
7596: free_matrix(dnewmpar,1,nlstate,1,nlstate);
1.126 brouard 7597:
7598: }
7599:
7600: /************ Variance of one-step probabilities ******************/
7601: void varprob(char optionfilefiname[], double **matcov, double x[], double delti[], int nlstate, double bage, double fage, int ij, int *Tvar, int **nbcode, int *ncodemax, char strstart[])
1.222 brouard 7602: {
7603: int i, j=0, k1, l1, tj;
7604: int k2, l2, j1, z1;
7605: int k=0, l;
7606: int first=1, first1, first2;
1.326 brouard 7607: int nres=0; /* New */
1.222 brouard 7608: double cv12, mu1, mu2, lc1, lc2, v12, v21, v11, v22,v1,v2, c12, tnalp;
7609: double **dnewm,**doldm;
7610: double *xp;
7611: double *gp, *gm;
7612: double **gradg, **trgradg;
7613: double **mu;
7614: double age, cov[NCOVMAX+1];
7615: double std=2.0; /* Number of standard deviation wide of confidence ellipsoids */
7616: int theta;
7617: char fileresprob[FILENAMELENGTH];
7618: char fileresprobcov[FILENAMELENGTH];
7619: char fileresprobcor[FILENAMELENGTH];
7620: double ***varpij;
7621:
7622: strcpy(fileresprob,"PROB_");
7623: strcat(fileresprob,fileres);
7624: if((ficresprob=fopen(fileresprob,"w"))==NULL) {
7625: printf("Problem with resultfile: %s\n", fileresprob);
7626: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprob);
7627: }
7628: strcpy(fileresprobcov,"PROBCOV_");
7629: strcat(fileresprobcov,fileresu);
7630: if((ficresprobcov=fopen(fileresprobcov,"w"))==NULL) {
7631: printf("Problem with resultfile: %s\n", fileresprobcov);
7632: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcov);
7633: }
7634: strcpy(fileresprobcor,"PROBCOR_");
7635: strcat(fileresprobcor,fileresu);
7636: if((ficresprobcor=fopen(fileresprobcor,"w"))==NULL) {
7637: printf("Problem with resultfile: %s\n", fileresprobcor);
7638: fprintf(ficlog,"Problem with resultfile: %s\n", fileresprobcor);
7639: }
7640: printf("Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7641: fprintf(ficlog,"Computing standard deviation of one-step probabilities: result on file '%s' \n",fileresprob);
7642: printf("Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7643: fprintf(ficlog,"Computing matrix of variance covariance of one-step probabilities: result on file '%s' \n",fileresprobcov);
7644: printf("and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7645: fprintf(ficlog,"and correlation matrix of one-step probabilities: result on file '%s' \n",fileresprobcor);
7646: pstamp(ficresprob);
7647: fprintf(ficresprob,"#One-step probabilities and stand. devi in ()\n");
7648: fprintf(ficresprob,"# Age");
7649: pstamp(ficresprobcov);
7650: fprintf(ficresprobcov,"#One-step probabilities and covariance matrix\n");
7651: fprintf(ficresprobcov,"# Age");
7652: pstamp(ficresprobcor);
7653: fprintf(ficresprobcor,"#One-step probabilities and correlation matrix\n");
7654: fprintf(ficresprobcor,"# Age");
1.126 brouard 7655:
7656:
1.222 brouard 7657: for(i=1; i<=nlstate;i++)
7658: for(j=1; j<=(nlstate+ndeath);j++){
7659: fprintf(ficresprob," p%1d-%1d (SE)",i,j);
7660: fprintf(ficresprobcov," p%1d-%1d ",i,j);
7661: fprintf(ficresprobcor," p%1d-%1d ",i,j);
7662: }
7663: /* fprintf(ficresprob,"\n");
7664: fprintf(ficresprobcov,"\n");
7665: fprintf(ficresprobcor,"\n");
7666: */
7667: xp=vector(1,npar);
7668: dnewm=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7669: doldm=matrix(1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
7670: mu=matrix(1,(nlstate)*(nlstate+ndeath), (int) bage, (int)fage);
7671: varpij=ma3x(1,nlstate*(nlstate+ndeath),1,nlstate*(nlstate+ndeath),(int) bage, (int) fage);
7672: first=1;
7673: fprintf(ficgp,"\n# Routine varprob");
7674: fprintf(fichtm,"\n<li><h4> Computing and drawing one step probabilities with their confidence intervals</h4></li>\n");
7675: fprintf(fichtm,"\n");
7676:
1.288 brouard 7677: fprintf(fichtm,"\n<li><h4> <a href=\"%s\">Matrix of variance-covariance of one-step probabilities (drawings)</a></h4> this page is important in order to visualize confidence intervals and especially correlation between disability and recovery, or more generally, way in and way back. File %s</li>\n",optionfilehtmcov,optionfilehtmcov);
1.222 brouard 7678: fprintf(fichtmcov,"Current page is file <a href=\"%s\">%s</a><br>\n\n<h4>Matrix of variance-covariance of pairs of step probabilities</h4>\n",optionfilehtmcov, optionfilehtmcov);
7679: fprintf(fichtmcov,"\nEllipsoids of confidence centered on point (p<inf>ij</inf>, p<inf>kl</inf>) are estimated \
1.126 brouard 7680: and drawn. It helps understanding how is the covariance between two incidences.\
7681: They are expressed in year<sup>-1</sup> in order to be less dependent of stepm.<br>\n");
1.222 brouard 7682: fprintf(fichtmcov,"\n<br> Contour plot corresponding to x'cov<sup>-1</sup>x = 4 (where x is the column vector (pij,pkl)) are drawn. \
1.126 brouard 7683: It can be understood this way: if pij and pkl where uncorrelated the (2x2) matrix of covariance \
7684: would have been (1/(var pij), 0 , 0, 1/(var pkl)), and the confidence interval would be 2 \
7685: standard deviations wide on each axis. <br>\
7686: Now, if both incidences are correlated (usual case) we diagonalised the inverse of the covariance matrix\
7687: and made the appropriate rotation to look at the uncorrelated principal directions.<br>\
7688: To be simple, these graphs help to understand the significativity of each parameter in relation to a second other one.<br> \n");
7689:
1.222 brouard 7690: cov[1]=1;
7691: /* tj=cptcoveff; */
1.225 brouard 7692: tj = (int) pow(2,cptcoveff);
1.222 brouard 7693: if (cptcovn<1) {tj=1;ncodemax[1]=1;}
7694: j1=0;
1.332 brouard 7695:
7696: for(nres=1;nres <=nresult; nres++){ /* For each resultline */
7697: for(j1=1; j1<=tj;j1++){ /* For any combination of dummy covariates, fixed and varying */
1.342 brouard 7698: /* printf("Varprob TKresult[nres]=%d j1=%d, nres=%d, cptcovn=%d, cptcoveff=%d tj=%d cptcovs=%d\n", TKresult[nres], j1, nres, cptcovn, cptcoveff, tj, cptcovs); */
1.332 brouard 7699: if(tj != 1 && TKresult[nres]!= j1)
7700: continue;
7701:
7702: /* for(j1=1; j1<=tj;j1++){ /\* For each valid combination of covariates or only once*\/ */
7703: /* for(nres=1;nres <=1; nres++){ /\* For each resultline *\/ */
7704: /* /\* for(nres=1;nres <=nresult; nres++){ /\\* For each resultline *\\/ *\/ */
1.222 brouard 7705: if (cptcovn>0) {
1.334 brouard 7706: fprintf(ficresprob, "\n#********** Variable ");
7707: fprintf(ficresprobcov, "\n#********** Variable ");
7708: fprintf(ficgp, "\n#********** Variable ");
7709: fprintf(fichtmcov, "\n<hr size=\"2\" color=\"#EC5E5E\">********** Variable ");
7710: fprintf(ficresprobcor, "\n#********** Variable ");
7711:
7712: /* Including quantitative variables of the resultline to be done */
7713: for (z1=1; z1<=cptcovs; z1++){ /* Loop on each variable of this resultline */
1.343 brouard 7714: /* printf("Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model); */
1.338 brouard 7715: fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s \n",nres, z1, modelresult[nres][z1], model);
7716: /* fprintf(ficlog,"Varprob modelresult[%d][%d]=%d model=1+age+%s resultline[%d]=%s \n",nres, z1, modelresult[nres][z1], model, nres, resultline[nres]); */
1.334 brouard 7717: if(Dummy[modelresult[nres][z1]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to z1 in resultline */
7718: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed referenced to model equation */
7719: fprintf(ficresprob,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
7720: fprintf(ficresprobcov,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
7721: fprintf(ficgp,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
7722: fprintf(fichtmcov,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
7723: fprintf(ficresprobcor,"V%d=%d ",Tvresult[nres][z1],Tresult[nres][z1]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
7724: fprintf(ficresprob,"fixed ");
7725: fprintf(ficresprobcov,"fixed ");
7726: fprintf(ficgp,"fixed ");
7727: fprintf(fichtmcov,"fixed ");
7728: fprintf(ficresprobcor,"fixed ");
7729: }else{
7730: fprintf(ficresprob,"varyi ");
7731: fprintf(ficresprobcov,"varyi ");
7732: fprintf(ficgp,"varyi ");
7733: fprintf(fichtmcov,"varyi ");
7734: fprintf(ficresprobcor,"varyi ");
7735: }
7736: }else if(Dummy[modelresult[nres][z1]]==1){ /* Quanti variable */
7737: /* For each selected (single) quantitative value */
1.337 brouard 7738: fprintf(ficresprob," V%d=%lg ",Tvqresult[nres][z1],Tqresult[nres][z1]);
1.334 brouard 7739: if(Fixed[modelresult[nres][z1]]==0){ /* Fixed */
7740: fprintf(ficresprob,"fixed ");
7741: fprintf(ficresprobcov,"fixed ");
7742: fprintf(ficgp,"fixed ");
7743: fprintf(fichtmcov,"fixed ");
7744: fprintf(ficresprobcor,"fixed ");
7745: }else{
7746: fprintf(ficresprob,"varyi ");
7747: fprintf(ficresprobcov,"varyi ");
7748: fprintf(ficgp,"varyi ");
7749: fprintf(fichtmcov,"varyi ");
7750: fprintf(ficresprobcor,"varyi ");
7751: }
7752: }else{
7753: printf("Error in varprob() Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=V%d cptcovs=%d, cptcoveff=%d \n", nres, z1, Dummy[modelresult[nres][z1]],nres,z1,modelresult[nres][z1],cptcovs, cptcoveff); /* end if dummy or quanti */
7754: fprintf(ficlog,"Error in varprob() Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=V%d cptcovs=%d, cptcoveff=%d \n", nres, z1, Dummy[modelresult[nres][z1]],nres,z1,modelresult[nres][z1],cptcovs, cptcoveff); /* end if dummy or quanti */
7755: exit(1);
7756: }
7757: } /* End loop on variable of this resultline */
7758: /* for (z1=1; z1<=cptcoveff; z1++) fprintf(ficresprob, "V%d=%d ",Tvaraff[z1],nbcode[Tvaraff[z1]][codtabm(j1,TnsdVar[Tvaraff[z1]])]); */
1.222 brouard 7759: fprintf(ficresprob, "**********\n#\n");
7760: fprintf(ficresprobcov, "**********\n#\n");
7761: fprintf(ficgp, "**********\n#\n");
7762: fprintf(fichtmcov, "**********\n<hr size=\"2\" color=\"#EC5E5E\">");
7763: fprintf(ficresprobcor, "**********\n#");
7764: if(invalidvarcomb[j1]){
7765: fprintf(ficgp,"\n#Combination (%d) ignored because no cases \n",j1);
7766: fprintf(fichtmcov,"\n<h3>Combination (%d) ignored because no cases </h3>\n",j1);
7767: continue;
7768: }
7769: }
7770: gradg=matrix(1,npar,1,(nlstate)*(nlstate+ndeath));
7771: trgradg=matrix(1,(nlstate)*(nlstate+ndeath),1,npar);
7772: gp=vector(1,(nlstate)*(nlstate+ndeath));
7773: gm=vector(1,(nlstate)*(nlstate+ndeath));
1.334 brouard 7774: for (age=bage; age<=fage; age ++){ /* Fo each age we feed the model equation with covariates, using precov as in hpxij() ? */
1.222 brouard 7775: cov[2]=age;
7776: if(nagesqr==1)
7777: cov[3]= age*age;
1.334 brouard 7778: /* New code end of combination but for each resultline */
7779: for(k1=1;k1<=cptcovt;k1++){ /* loop on model equation (including products) */
1.349 brouard 7780: if(Typevar[k1]==1 || Typevar[k1] ==3){ /* A product with age */
1.334 brouard 7781: cov[2+nagesqr+k1]=precov[nres][k1]*cov[2];
1.326 brouard 7782: }else{
1.334 brouard 7783: cov[2+nagesqr+k1]=precov[nres][k1];
1.326 brouard 7784: }
1.334 brouard 7785: }/* End of loop on model equation */
7786: /* Old code */
7787: /* /\* for (k=1; k<=cptcovn;k++) { *\/ */
7788: /* /\* cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,k)]; *\/ */
7789: /* for (k=1; k<=nsd;k++) { /\* For single dummy covariates only *\/ */
7790: /* /\* Here comes the value of the covariate 'j1' after renumbering k with single dummy covariates *\/ */
7791: /* cov[2+nagesqr+TvarsDind[k]]=nbcode[TvarsD[k]][codtabm(j1,TnsdVar[TvarsD[k]])]; */
7792: /* /\*cov[2+nagesqr+k]=nbcode[Tvar[k]][codtabm(j1,Tvar[k])];*\//\* j1 1 2 3 4 */
7793: /* * 1 1 1 1 1 */
7794: /* * 2 2 1 1 1 */
7795: /* * 3 1 2 1 1 */
7796: /* *\/ */
7797: /* /\* nbcode[1][1]=0 nbcode[1][2]=1;*\/ */
7798: /* } */
7799: /* /\* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
7800: /* /\* ) p nbcode[Tvar[Tage[k]]][(1 & (ij-1) >> (k-1))+1] *\/ */
7801: /* /\*for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=cov[2+Tage[k]]*cov[2]; *\/ */
7802: /* for (k=1; k<=cptcovage;k++){ /\* For product with age *\/ */
7803: /* if(Dummy[Tage[k]]==2){ /\* dummy with age *\/ */
7804: /* cov[2+nagesqr+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(j1,TnsdVar[Tvar[Tage[k]]])]*cov[2]; */
7805: /* /\* cov[++k1]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7806: /* } else if(Dummy[Tage[k]]==3){ /\* quantitative with age *\/ */
7807: /* printf("Internal IMaCh error, don't know which value for quantitative covariate with age, Tage[k]%d, k=%d, Tvar[Tage[k]]=V%d, age=%d\n",Tage[k],k ,Tvar[Tage[k]], (int)cov[2]); */
7808: /* /\* cov[2+nagesqr+Tage[k]]=meanq[k]/idq[k]*cov[2];/\\* Using the mean of quantitative variable Tvar[Tage[k]] /\\* Tqresult[nres][k]; *\\/ *\/ */
7809: /* /\* exit(1); *\/ */
7810: /* /\* cov[++k1]=Tqresult[nres][k]; *\/ */
7811: /* } */
7812: /* /\* cov[2+Tage[k]+nagesqr]=nbcode[Tvar[Tage[k]]][codtabm(ij,k)]*cov[2]; *\/ */
7813: /* } */
7814: /* for (k=1; k<=cptcovprod;k++){/\* For product without age *\/ */
7815: /* if(Dummy[Tvard[k][1]]==0){ */
7816: /* if(Dummy[Tvard[k][2]]==0){ */
7817: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])]; */
7818: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7819: /* }else{ /\* Should we use the mean of the quantitative variables? *\/ */
7820: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(j1,TnsdVar[Tvard[k][1]])] * Tqresult[nres][resultmodel[nres][k]]; */
7821: /* /\* cov[++k1]=nbcode[Tvard[k][1]][codtabm(ij,k)] * Tqresult[nres][k]; *\/ */
7822: /* } */
7823: /* }else{ */
7824: /* if(Dummy[Tvard[k][2]]==0){ */
7825: /* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][2]][codtabm(j1,TnsdVar[Tvard[k][2]])] * Tqinvresult[nres][TnsdVar[Tvard[k][1]]]; */
7826: /* /\* cov[++k1]=nbcode[Tvard[k][2]][codtabm(ij,k)] * Tqinvresult[nres][Tvard[k][1]]; *\/ */
7827: /* }else{ */
7828: /* cov[2+nagesqr+Tprod[k]]=Tqinvresult[nres][TnsdVar[Tvard[k][1]]]* Tqinvresult[nres][TnsdVar[Tvard[k][2]]]; */
7829: /* /\* cov[++k1]=Tqinvresult[nres][Tvard[k][1]]* Tqinvresult[nres][Tvard[k][2]]; *\/ */
7830: /* } */
7831: /* } */
7832: /* /\* cov[2+nagesqr+Tprod[k]]=nbcode[Tvard[k][1]][codtabm(ij,k)]*nbcode[Tvard[k][2]][codtabm(ij,k)]; *\/ */
7833: /* } */
1.326 brouard 7834: /* For each age and combination of dummy covariates we slightly move the parameters of delti in order to get the gradient*/
1.222 brouard 7835: for(theta=1; theta <=npar; theta++){
7836: for(i=1; i<=npar; i++)
7837: xp[i] = x[i] + (i==theta ?delti[theta]:(double)0);
1.220 brouard 7838:
1.222 brouard 7839: pmij(pmmij,cov,ncovmodel,xp,nlstate);
1.220 brouard 7840:
1.222 brouard 7841: k=0;
7842: for(i=1; i<= (nlstate); i++){
7843: for(j=1; j<=(nlstate+ndeath);j++){
7844: k=k+1;
7845: gp[k]=pmmij[i][j];
7846: }
7847: }
1.220 brouard 7848:
1.222 brouard 7849: for(i=1; i<=npar; i++)
7850: xp[i] = x[i] - (i==theta ?delti[theta]:(double)0);
1.220 brouard 7851:
1.222 brouard 7852: pmij(pmmij,cov,ncovmodel,xp,nlstate);
7853: k=0;
7854: for(i=1; i<=(nlstate); i++){
7855: for(j=1; j<=(nlstate+ndeath);j++){
7856: k=k+1;
7857: gm[k]=pmmij[i][j];
7858: }
7859: }
1.220 brouard 7860:
1.222 brouard 7861: for(i=1; i<= (nlstate)*(nlstate+ndeath); i++)
7862: gradg[theta][i]=(gp[i]-gm[i])/(double)2./delti[theta];
7863: }
1.126 brouard 7864:
1.222 brouard 7865: for(j=1; j<=(nlstate)*(nlstate+ndeath);j++)
7866: for(theta=1; theta <=npar; theta++)
7867: trgradg[j][theta]=gradg[theta][j];
1.220 brouard 7868:
1.222 brouard 7869: matprod2(dnewm,trgradg,1,(nlstate)*(nlstate+ndeath),1,npar,1,npar,matcov);
7870: matprod2(doldm,dnewm,1,(nlstate)*(nlstate+ndeath),1,npar,1,(nlstate)*(nlstate+ndeath),gradg);
1.220 brouard 7871:
1.222 brouard 7872: pmij(pmmij,cov,ncovmodel,x,nlstate);
1.220 brouard 7873:
1.222 brouard 7874: k=0;
7875: for(i=1; i<=(nlstate); i++){
7876: for(j=1; j<=(nlstate+ndeath);j++){
7877: k=k+1;
7878: mu[k][(int) age]=pmmij[i][j];
7879: }
7880: }
7881: for(i=1;i<=(nlstate)*(nlstate+ndeath);i++)
7882: for(j=1;j<=(nlstate)*(nlstate+ndeath);j++)
7883: varpij[i][j][(int)age] = doldm[i][j];
1.220 brouard 7884:
1.222 brouard 7885: /*printf("\n%d ",(int)age);
7886: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7887: printf("%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7888: fprintf(ficlog,"%e [%e ;%e] ",gm[i],gm[i]-2*sqrt(doldm[i][i]),gm[i]+2*sqrt(doldm[i][i]));
7889: }*/
1.220 brouard 7890:
1.222 brouard 7891: fprintf(ficresprob,"\n%d ",(int)age);
7892: fprintf(ficresprobcov,"\n%d ",(int)age);
7893: fprintf(ficresprobcor,"\n%d ",(int)age);
1.220 brouard 7894:
1.222 brouard 7895: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++)
7896: fprintf(ficresprob,"%11.3e (%11.3e) ",mu[i][(int) age],sqrt(varpij[i][i][(int)age]));
7897: for (i=1; i<=(nlstate)*(nlstate+ndeath);i++){
7898: fprintf(ficresprobcov,"%11.3e ",mu[i][(int) age]);
7899: fprintf(ficresprobcor,"%11.3e ",mu[i][(int) age]);
7900: }
7901: i=0;
7902: for (k=1; k<=(nlstate);k++){
7903: for (l=1; l<=(nlstate+ndeath);l++){
7904: i++;
7905: fprintf(ficresprobcov,"\n%d %d-%d",(int)age,k,l);
7906: fprintf(ficresprobcor,"\n%d %d-%d",(int)age,k,l);
7907: for (j=1; j<=i;j++){
7908: /* printf(" k=%d l=%d i=%d j=%d\n",k,l,i,j);fflush(stdout); */
7909: fprintf(ficresprobcov," %11.3e",varpij[i][j][(int)age]);
7910: fprintf(ficresprobcor," %11.3e",varpij[i][j][(int) age]/sqrt(varpij[i][i][(int) age])/sqrt(varpij[j][j][(int)age]));
7911: }
7912: }
7913: }/* end of loop for state */
7914: } /* end of loop for age */
7915: free_vector(gp,1,(nlstate+ndeath)*(nlstate+ndeath));
7916: free_vector(gm,1,(nlstate+ndeath)*(nlstate+ndeath));
7917: free_matrix(trgradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7918: free_matrix(gradg,1,(nlstate+ndeath)*(nlstate+ndeath),1,npar);
7919:
7920: /* Confidence intervalle of pij */
7921: /*
7922: fprintf(ficgp,"\nunset parametric;unset label");
7923: fprintf(ficgp,"\nset log y;unset log x; set xlabel \"Age\";set ylabel \"probability (year-1)\"");
7924: fprintf(ficgp,"\nset ter png small\nset size 0.65,0.65");
7925: fprintf(fichtm,"\n<br>Probability with confidence intervals expressed in year<sup>-1</sup> :<a href=\"pijgr%s.png\">pijgr%s.png</A>, ",optionfilefiname,optionfilefiname);
7926: fprintf(fichtm,"\n<br><img src=\"pijgr%s.png\"> ",optionfilefiname);
7927: fprintf(ficgp,"\nset out \"pijgr%s.png\"",optionfilefiname);
7928: fprintf(ficgp,"\nplot \"%s\" every :::%d::%d u 1:2 \"\%%lf",k1,k2,xfilevarprob);
7929: */
7930:
7931: /* Drawing ellipsoids of confidence of two variables p(k1-l1,k2-l2)*/
7932: first1=1;first2=2;
7933: for (k2=1; k2<=(nlstate);k2++){
7934: for (l2=1; l2<=(nlstate+ndeath);l2++){
7935: if(l2==k2) continue;
7936: j=(k2-1)*(nlstate+ndeath)+l2;
7937: for (k1=1; k1<=(nlstate);k1++){
7938: for (l1=1; l1<=(nlstate+ndeath);l1++){
7939: if(l1==k1) continue;
7940: i=(k1-1)*(nlstate+ndeath)+l1;
7941: if(i<=j) continue;
7942: for (age=bage; age<=fage; age ++){
7943: if ((int)age %5==0){
7944: v1=varpij[i][i][(int)age]/stepm*YEARM/stepm*YEARM;
7945: v2=varpij[j][j][(int)age]/stepm*YEARM/stepm*YEARM;
7946: cv12=varpij[i][j][(int)age]/stepm*YEARM/stepm*YEARM;
7947: mu1=mu[i][(int) age]/stepm*YEARM ;
7948: mu2=mu[j][(int) age]/stepm*YEARM;
7949: c12=cv12/sqrt(v1*v2);
7950: /* Computing eigen value of matrix of covariance */
7951: lc1=((v1+v2)+sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7952: lc2=((v1+v2)-sqrt((v1+v2)*(v1+v2) - 4*(v1*v2-cv12*cv12)))/2.;
7953: if ((lc2 <0) || (lc1 <0) ){
7954: if(first2==1){
7955: first1=0;
7956: printf("Strange: j1=%d One eigen value of 2x2 matrix of covariance is negative, lc1=%11.3e, lc2=%11.3e, v1=%11.3e, v2=%11.3e, cv12=%11.3e.\n It means that the matrix was not well estimated (varpij), for i=%2d, j=%2d, age=%4d .\n See files %s and %s. Probably WRONG RESULTS. See log file for details...\n", j1, lc1, lc2, v1, v2, cv12, i, j, (int)age,fileresprobcov, fileresprobcor);
7957: }
7958: fprintf(ficlog,"Strange: j1=%d One eigen value of 2x2 matrix of covariance is negative, lc1=%11.3e, lc2=%11.3e, v1=%11.3e, v2=%11.3e, cv12=%11.3e.\n It means that the matrix was not well estimated (varpij), for i=%2d, j=%2d, age=%4d .\n See files %s and %s. Probably WRONG RESULTS.\n", j1, lc1, lc2, v1, v2, cv12, i, j, (int)age,fileresprobcov, fileresprobcor);fflush(ficlog);
7959: /* lc1=fabs(lc1); */ /* If we want to have them positive */
7960: /* lc2=fabs(lc2); */
7961: }
1.220 brouard 7962:
1.222 brouard 7963: /* Eigen vectors */
1.280 brouard 7964: if(1+(v1-lc1)*(v1-lc1)/cv12/cv12 <1.e-5){
7965: printf(" Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7966: fprintf(ficlog," Error sqrt of a negative number: %lf\n",1+(v1-lc1)*(v1-lc1)/cv12/cv12);
7967: v11=(1./sqrt(fabs(1+(v1-lc1)*(v1-lc1)/cv12/cv12)));
7968: }else
7969: v11=(1./sqrt(1+(v1-lc1)*(v1-lc1)/cv12/cv12));
1.222 brouard 7970: /*v21=sqrt(1.-v11*v11); *//* error */
7971: v21=(lc1-v1)/cv12*v11;
7972: v12=-v21;
7973: v22=v11;
7974: tnalp=v21/v11;
7975: if(first1==1){
7976: first1=0;
7977: printf("%d %d%d-%d%d mu %.4e %.4e Var %.4e %.4e cor %.3f cov %.4e Eig %.3e %.3e 1stv %.3f %.3f tang %.3f\nOthers in log...\n",(int) age,k1,l1,k2,l2,mu1,mu2,v1,v2,c12,cv12,lc1,lc2,v11,v21,tnalp);
7978: }
7979: fprintf(ficlog,"%d %d%d-%d%d mu %.4e %.4e Var %.4e %.4e cor %.3f cov %.4e Eig %.3e %.3e 1stv %.3f %.3f tan %.3f\n",(int) age,k1,l1,k2,l2,mu1,mu2,v1,v2,c12,cv12,lc1,lc2,v11,v21,tnalp);
7980: /*printf(fignu*/
7981: /* mu1+ v11*lc1*cost + v12*lc2*sin(t) */
7982: /* mu2+ v21*lc1*cost + v22*lc2*sin(t) */
7983: if(first==1){
7984: first=0;
7985: fprintf(ficgp,"\n# Ellipsoids of confidence\n#\n");
7986: fprintf(ficgp,"\nset parametric;unset label");
7987: fprintf(ficgp,"\nset log y;set log x; set xlabel \"p%1d%1d (year-1)\";set ylabel \"p%1d%1d (year-1)\"",k1,l1,k2,l2);
7988: fprintf(ficgp,"\nset ter svg size 640, 480");
1.266 brouard 7989: fprintf(fichtmcov,"\n<p><br>Ellipsoids of confidence cov(p%1d%1d,p%1d%1d) expressed in year<sup>-1</sup>\
1.220 brouard 7990: :<a href=\"%s_%d%1d%1d-%1d%1d.svg\"> \
1.201 brouard 7991: %s_%d%1d%1d-%1d%1d.svg</A>, ",k1,l1,k2,l2,\
1.222 brouard 7992: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2, \
7993: subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7994: fprintf(fichtmcov,"\n<br><img src=\"%s_%d%1d%1d-%1d%1d.svg\"> ",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7995: fprintf(fichtmcov,"\n<br> Correlation at age %d (%.3f),",(int) age, c12);
7996: fprintf(ficgp,"\nset out \"%s_%d%1d%1d-%1d%1d.svg\"",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
7997: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
7998: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
7999: fprintf(ficgp,"\nplot [-pi:pi] %11.3e+ %.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)), %11.3e +%.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)) not", \
1.280 brouard 8000: mu1,std,v11,sqrt(fabs(lc1)),v12,sqrt(fabs(lc2)), \
8001: mu2,std,v21,sqrt(fabs(lc1)),v22,sqrt(fabs(lc2))); /* For gnuplot only */
1.222 brouard 8002: }else{
8003: first=0;
8004: fprintf(fichtmcov," %d (%.3f),",(int) age, c12);
8005: fprintf(ficgp,"\n# Age %d, p%1d%1d - p%1d%1d",(int) age, k1,l1,k2,l2);
8006: fprintf(ficgp,"\nset label \"%d\" at %11.3e,%11.3e center",(int) age, mu1,mu2);
8007: fprintf(ficgp,"\nreplot %11.3e+ %.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)), %11.3e +%.3f*(%11.3e*%11.3e*cos(t)+%11.3e*%11.3e*sin(t)) not", \
1.266 brouard 8008: mu1,std,v11,sqrt(lc1),v12,sqrt(fabs(lc2)), \
8009: mu2,std,v21,sqrt(lc1),v22,sqrt(fabs(lc2)));
1.222 brouard 8010: }/* if first */
8011: } /* age mod 5 */
8012: } /* end loop age */
8013: fprintf(ficgp,"\nset out;\nset out \"%s_%d%1d%1d-%1d%1d.svg\";replot;set out;",subdirf2(optionfilefiname,"VARPIJGR_"), j1,k1,l1,k2,l2);
8014: first=1;
8015: } /*l12 */
8016: } /* k12 */
8017: } /*l1 */
8018: }/* k1 */
1.332 brouard 8019: } /* loop on combination of covariates j1 */
1.326 brouard 8020: } /* loop on nres */
1.222 brouard 8021: free_ma3x(varpij,1,nlstate,1,nlstate+ndeath,(int) bage, (int)fage);
8022: free_matrix(mu,1,(nlstate+ndeath)*(nlstate+ndeath),(int) bage, (int)fage);
8023: free_matrix(doldm,1,(nlstate)*(nlstate+ndeath),1,(nlstate)*(nlstate+ndeath));
8024: free_matrix(dnewm,1,(nlstate)*(nlstate+ndeath),1,npar);
8025: free_vector(xp,1,npar);
8026: fclose(ficresprob);
8027: fclose(ficresprobcov);
8028: fclose(ficresprobcor);
8029: fflush(ficgp);
8030: fflush(fichtmcov);
8031: }
1.126 brouard 8032:
8033:
8034: /******************* Printing html file ***********/
1.201 brouard 8035: void printinghtml(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 8036: int lastpass, int stepm, int weightopt, char model[],\
8037: int imx,int jmin, int jmax, double jmeanint,char rfileres[],\
1.296 brouard 8038: int popforecast, int mobilav, int prevfcast, int mobilavproj, int prevbcast, int estepm , \
8039: double jprev1, double mprev1,double anprev1, double dateprev1, double dateprojd, double dateback1, \
8040: double jprev2, double mprev2,double anprev2, double dateprev2, double dateprojf, double dateback2){
1.237 brouard 8041: int jj1, k1, i1, cpt, k4, nres;
1.319 brouard 8042: /* In fact some results are already printed in fichtm which is open */
1.126 brouard 8043: fprintf(fichtm,"<ul><li><a href='#firstorder'>Result files (first order: no variance)</a>\n \
8044: <li><a href='#secondorder'>Result files (second order (variance)</a>\n \
8045: </ul>");
1.319 brouard 8046: /* fprintf(fichtm,"<ul><li> model=1+age+%s\n \ */
8047: /* </ul>", model); */
1.214 brouard 8048: fprintf(fichtm,"<ul><li><h4><a name='firstorder'>Result files (first order: no variance)</a></h4>\n");
8049: fprintf(fichtm,"<li>- Observed frequency between two states (during the period defined between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf): <a href=\"%s\">%s</a> (html file)<br/>\n",
8050: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTMFR_",".htm"),subdirfext3(optionfilefiname,"PHTMFR_",".htm"));
1.332 brouard 8051: fprintf(fichtm,"<li> - Observed prevalence (cross-sectional prevalence) in each state (during the period defined between %.lf/%.lf/%.lf and %.lf/%.lf/%.lf): <a href=\"%s\">%s</a> (html file) ",
1.213 brouard 8052: jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,subdirfext3(optionfilefiname,"PHTM_",".htm"),subdirfext3(optionfilefiname,"PHTM_",".htm"));
8053: fprintf(fichtm,", <a href=\"%s\">%s</a> (text file) <br>\n",subdirf2(fileresu,"P_"),subdirf2(fileresu,"P_"));
1.126 brouard 8054: fprintf(fichtm,"\
8055: - Estimated transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
1.201 brouard 8056: stepm,subdirf2(fileresu,"PIJ_"),subdirf2(fileresu,"PIJ_"));
1.126 brouard 8057: fprintf(fichtm,"\
1.217 brouard 8058: - Estimated back transition probabilities over %d (stepm) months: <a href=\"%s\">%s</a><br>\n ",
8059: stepm,subdirf2(fileresu,"PIJB_"),subdirf2(fileresu,"PIJB_"));
8060: fprintf(fichtm,"\
1.288 brouard 8061: - Period (forward) prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8062: subdirf2(fileresu,"PL_"),subdirf2(fileresu,"PL_"));
1.126 brouard 8063: fprintf(fichtm,"\
1.288 brouard 8064: - Backward prevalence in each health state: <a href=\"%s\">%s</a> <br>\n",
1.217 brouard 8065: subdirf2(fileresu,"PLB_"),subdirf2(fileresu,"PLB_"));
8066: fprintf(fichtm,"\
1.211 brouard 8067: - (a) Life expectancies by health status at initial age, e<sub>i.</sub> (b) health expectancies by health status at initial age, e<sub>ij</sub> . If one or more covariates are included, specific tables for each value of the covariate are output in sequences within the same file (estepm=%2d months): \
1.126 brouard 8068: <a href=\"%s\">%s</a> <br>\n",
1.201 brouard 8069: estepm,subdirf2(fileresu,"E_"),subdirf2(fileresu,"E_"));
1.211 brouard 8070: if(prevfcast==1){
8071: fprintf(fichtm,"\
8072: - Prevalence projections by age and states: \
1.201 brouard 8073: <a href=\"%s\">%s</a> <br>\n</li>", subdirf2(fileresu,"F_"),subdirf2(fileresu,"F_"));
1.211 brouard 8074: }
1.126 brouard 8075:
8076:
1.225 brouard 8077: m=pow(2,cptcoveff);
1.222 brouard 8078: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8079:
1.317 brouard 8080: fprintf(fichtm," \n<ul><li><b>Graphs (first order)</b></li><p>");
1.264 brouard 8081:
8082: jj1=0;
8083:
8084: fprintf(fichtm," \n<ul>");
1.337 brouard 8085: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8086: /* k1=nres; */
1.338 brouard 8087: k1=TKresult[nres];
8088: if(TKresult[nres]==0)k1=1; /* To be checked for no result */
1.337 brouard 8089: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8090: /* if(m != 1 && TKresult[nres]!= k1) */
8091: /* continue; */
1.264 brouard 8092: jj1++;
8093: if (cptcovn > 0) {
8094: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescov");
1.337 brouard 8095: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
8096: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8097: }
1.337 brouard 8098: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8099: /* fprintf(fichtm,"_V%d=%d_",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8100: /* } */
8101: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8102: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8103: /* } */
1.264 brouard 8104: fprintf(fichtm,"\">");
8105:
8106: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8107: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8108: for (cpt=1; cpt<=cptcovs;cpt++){
8109: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8110: }
1.337 brouard 8111: /* fprintf(fichtm,"************ Results for covariates"); */
8112: /* for (cpt=1; cpt<=cptcoveff;cpt++){ */
8113: /* fprintf(fichtm," V%d=%d ",Tvresult[nres][cpt],(int)Tresult[nres][cpt]); */
8114: /* } */
8115: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8116: /* fprintf(fichtm," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8117: /* } */
1.264 brouard 8118: if(invalidvarcomb[k1]){
8119: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8120: continue;
8121: }
8122: fprintf(fichtm,"</a></li>");
8123: } /* cptcovn >0 */
8124: }
1.317 brouard 8125: fprintf(fichtm," \n</ul>");
1.264 brouard 8126:
1.222 brouard 8127: jj1=0;
1.237 brouard 8128:
1.337 brouard 8129: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8130: /* k1=nres; */
1.338 brouard 8131: k1=TKresult[nres];
8132: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8133: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8134: /* if(m != 1 && TKresult[nres]!= k1) */
8135: /* continue; */
1.220 brouard 8136:
1.222 brouard 8137: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8138: jj1++;
8139: if (cptcovn > 0) {
1.264 brouard 8140: fprintf(fichtm,"\n<p><a name=\"rescov");
1.337 brouard 8141: for (cpt=1; cpt<=cptcovs;cpt++){
8142: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.264 brouard 8143: }
1.337 brouard 8144: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8145: /* fprintf(fichtm,"_V%d=%f_",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8146: /* } */
1.264 brouard 8147: fprintf(fichtm,"\"</a>");
8148:
1.222 brouard 8149: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8150: for (cpt=1; cpt<=cptcovs;cpt++){
8151: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8152: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8153: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
8154: /* printf(" V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]);fflush(stdout); */
1.222 brouard 8155: }
1.230 brouard 8156: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
1.338 brouard 8157: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.222 brouard 8158: if(invalidvarcomb[k1]){
8159: fprintf(fichtm,"\n<h3>Combination (%d) ignored because no cases </h3>\n",k1);
8160: printf("\nCombination (%d) ignored because no cases \n",k1);
8161: continue;
8162: }
8163: }
8164: /* aij, bij */
1.259 brouard 8165: fprintf(fichtm,"<br>- Logit model (yours is: logit(pij)=log(pij/pii)= aij+ bij age+%s) as a function of age: <a href=\"%s_%d-1-%d.svg\">%s_%d-1-%d.svg</a><br> \
1.241 brouard 8166: <img src=\"%s_%d-1-%d.svg\">",model,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres);
1.222 brouard 8167: /* Pij */
1.241 brouard 8168: fprintf(fichtm,"<br>\n- P<sub>ij</sub> or conditional probabilities to be observed in state j being in state i, %d (stepm) months before: <a href=\"%s_%d-2-%d.svg\">%s_%d-2-%d.svg</a><br> \
8169: <img src=\"%s_%d-2-%d.svg\">",stepm,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres);
1.222 brouard 8170: /* Quasi-incidences */
8171: fprintf(fichtm,"<br>\n- I<sub>ij</sub> or Conditional probabilities to be observed in state j being in state i %d (stepm) months\
1.220 brouard 8172: before but expressed in per year i.e. quasi incidences if stepm is small and probabilities too, \
1.211 brouard 8173: incidence (rates) are the limit when h tends to zero of the ratio of the probability <sub>h</sub>P<sub>ij</sub> \
1.241 brouard 8174: divided by h: <sub>h</sub>P<sub>ij</sub>/h : <a href=\"%s_%d-3-%d.svg\">%s_%d-3-%d.svg</a><br> \
8175: <img src=\"%s_%d-3-%d.svg\">",stepm,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres,subdirf2(optionfilefiname,"PE_"),k1,nres);
1.222 brouard 8176: /* Survival functions (period) in state j */
8177: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8178: fprintf(fichtm,"<br>\n- Survival functions in state %d. And probability to be observed in state %d being in state (1 to %d) at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br>", cpt, cpt, nlstate, subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
8179: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8180: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.222 brouard 8181: }
8182: /* State specific survival functions (period) */
8183: for(cpt=1; cpt<=nlstate;cpt++){
1.292 brouard 8184: fprintf(fichtm,"<br>\n- Survival functions in state %d and in any other live state (total).\
8185: And probability to be observed in various states (up to %d) being in state %d at different ages. \
1.329 brouard 8186: <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br> ", cpt, nlstate, cpt, subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres,subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
8187: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
8188: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.222 brouard 8189: }
1.288 brouard 8190: /* Period (forward stable) prevalence in each health state */
1.222 brouard 8191: for(cpt=1; cpt<=nlstate;cpt++){
1.329 brouard 8192: fprintf(fichtm,"<br>\n- Convergence to period (stable) prevalence in state %d. Or probability for a person being in state (1 to %d) at different ages, to be in state %d some years after. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br>", cpt, nlstate, cpt, subdirf2(optionfilefiname,"P_"),cpt,k1,nres,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.338 brouard 8193: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJ_"),subdirf2(optionfilefiname,"PIJ_"));
1.329 brouard 8194: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.222 brouard 8195: }
1.296 brouard 8196: if(prevbcast==1){
1.288 brouard 8197: /* Backward prevalence in each health state */
1.222 brouard 8198: for(cpt=1; cpt<=nlstate;cpt++){
1.338 brouard 8199: fprintf(fichtm,"<br>\n- Convergence to mixed (stable) back prevalence in state %d. Or probability for a person to be in state %d at a younger age, knowing that she/he was in state (1 to %d) at different older ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a><br>", cpt, cpt, nlstate, subdirf2(optionfilefiname,"PB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
8200: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"PIJB_"),subdirf2(optionfilefiname,"PIJB_"));
8201: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">" ,subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.222 brouard 8202: }
1.217 brouard 8203: }
1.222 brouard 8204: if(prevfcast==1){
1.288 brouard 8205: /* Projection of prevalence up to period (forward stable) prevalence in each health state */
1.222 brouard 8206: for(cpt=1; cpt<=nlstate;cpt++){
1.314 brouard 8207: fprintf(fichtm,"<br>\n- Projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), from year %.1f up to year %.1f tending to period (stable) forward prevalence in state %d. Or probability to be in state %d being in an observed weighted state (from 1 to %d). <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a>", dateprev1, dateprev2, mobilavproj, dateprojd, dateprojf, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
8208: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"F_"),subdirf2(optionfilefiname,"F_"));
8209: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",
8210: subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.222 brouard 8211: }
8212: }
1.296 brouard 8213: if(prevbcast==1){
1.268 brouard 8214: /* Back projection of prevalence up to stable (mixed) back-prevalence in each health state */
8215: for(cpt=1; cpt<=nlstate;cpt++){
1.273 brouard 8216: fprintf(fichtm,"<br>\n- Back projection of cross-sectional prevalence (estimated with cases observed from %.1f to %.1f and mobil_average=%d), \
8217: from year %.1f up to year %.1f (probably close to stable [mixed] back prevalence in state %d (randomness in cross-sectional prevalence is not taken into \
8218: account but can visually be appreciated). Or probability to have been in an state %d, knowing that the person was in either state (1 or %d) \
1.314 brouard 8219: with weights corresponding to observed prevalence at different ages. <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a>", dateprev1, dateprev2, mobilavproj, dateback1, dateback2, cpt, cpt, nlstate, subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres,subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
8220: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>)\n<br>",subdirf2(optionfilefiname,"FB_"),subdirf2(optionfilefiname,"FB_"));
8221: fprintf(fichtm," <img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
1.268 brouard 8222: }
8223: }
1.220 brouard 8224:
1.222 brouard 8225: for(cpt=1; cpt<=nlstate;cpt++) {
1.314 brouard 8226: fprintf(fichtm,"\n<br>- Life expectancy by health state (%d) at initial age and its decomposition into health expectancies in each alive state (1 to %d) (or area under each survival functions): <a href=\"%s_%d-%d-%d.svg\">%s_%d-%d-%d.svg</a>",cpt,nlstate,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres,subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
8227: fprintf(fichtm," (data from text file <a href=\"%s.txt\"> %s.txt</a>)\n<br>",subdirf2(optionfilefiname,"E_"),subdirf2(optionfilefiname,"E_"));
8228: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">", subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres );
1.222 brouard 8229: }
8230: /* } /\* end i1 *\/ */
1.337 brouard 8231: }/* End k1=nres */
1.222 brouard 8232: fprintf(fichtm,"</ul>");
1.126 brouard 8233:
1.222 brouard 8234: fprintf(fichtm,"\
1.126 brouard 8235: \n<br><li><h4> <a name='secondorder'>Result files (second order: variances)</a></h4>\n\
1.193 brouard 8236: - Parameter file with estimated parameters and covariance matrix: <a href=\"%s\">%s</a> <br> \
1.203 brouard 8237: - 95%% confidence intervals and Wald tests of the estimated parameters are in the log file if optimization has been done (mle != 0).<br> \
1.197 brouard 8238: But because parameters are usually highly correlated (a higher incidence of disability \
8239: and a higher incidence of recovery can give very close observed transition) it might \
8240: be very useful to look not only at linear confidence intervals estimated from the \
8241: variances but at the covariance matrix. And instead of looking at the estimated coefficients \
8242: (parameters) of the logistic regression, it might be more meaningful to visualize the \
8243: covariance matrix of the one-step probabilities. \
8244: See page 'Matrix of variance-covariance of one-step probabilities' below. \n", rfileres,rfileres);
1.126 brouard 8245:
1.222 brouard 8246: fprintf(fichtm," - Standard deviation of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
8247: subdirf2(fileresu,"PROB_"),subdirf2(fileresu,"PROB_"));
8248: fprintf(fichtm,"\
1.126 brouard 8249: - Variance-covariance of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8250: subdirf2(fileresu,"PROBCOV_"),subdirf2(fileresu,"PROBCOV_"));
1.126 brouard 8251:
1.222 brouard 8252: fprintf(fichtm,"\
1.126 brouard 8253: - Correlation matrix of one-step probabilities: <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8254: subdirf2(fileresu,"PROBCOR_"),subdirf2(fileresu,"PROBCOR_"));
8255: fprintf(fichtm,"\
1.126 brouard 8256: - Variances and covariances of health expectancies by age and <b>initial health status</b> (cov(e<sup>ij</sup>,e<sup>kl</sup>)(estepm=%2d months): \
8257: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8258: estepm,subdirf2(fileresu,"CVE_"),subdirf2(fileresu,"CVE_"));
1.222 brouard 8259: fprintf(fichtm,"\
1.126 brouard 8260: - (a) Health expectancies by health status at initial age (e<sup>ij</sup>) and standard errors (in parentheses) (b) life expectancies and standard errors (e<sup>i.</sup>=e<sup>i1</sup>+e<sup>i2</sup>+...)(estepm=%2d months): \
8261: <a href=\"%s\">%s</a> <br>\n</li>",
1.201 brouard 8262: estepm,subdirf2(fileresu,"STDE_"),subdirf2(fileresu,"STDE_"));
1.222 brouard 8263: fprintf(fichtm,"\
1.288 brouard 8264: - Variances and covariances of health expectancies by age. Status (i) based health expectancies (in state j), e<sup>ij</sup> are weighted by the forward (period) prevalences in each state i (if popbased=1, an additional computation is done using the cross-sectional prevalences, i.e population based) (estepm=%d months): <a href=\"%s\">%s</a><br>\n",
1.222 brouard 8265: estepm, subdirf2(fileresu,"V_"),subdirf2(fileresu,"V_"));
8266: fprintf(fichtm,"\
1.128 brouard 8267: - Total life expectancy and total health expectancies to be spent in each health state e<sup>.j</sup> with their standard errors (if popbased=1, an additional computation is done using the cross-sectional prevalences, i.e population based) (estepm=%d months): <a href=\"%s\">%s</a> <br>\n",
1.222 brouard 8268: estepm, subdirf2(fileresu,"T_"),subdirf2(fileresu,"T_"));
8269: fprintf(fichtm,"\
1.288 brouard 8270: - Standard deviation of forward (period) prevalences: <a href=\"%s\">%s</a> <br>\n",\
1.222 brouard 8271: subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
1.126 brouard 8272:
8273: /* if(popforecast==1) fprintf(fichtm,"\n */
8274: /* - Prevalences forecasting: <a href=\"f%s\">f%s</a> <br>\n */
8275: /* - Population forecasting (if popforecast=1): <a href=\"pop%s\">pop%s</a> <br>\n */
8276: /* <br>",fileres,fileres,fileres,fileres); */
8277: /* else */
1.338 brouard 8278: /* fprintf(fichtm,"\n No population forecast: popforecast = %d (instead of 1) or stepm = %d (instead of 1) or model=1+age+%s (instead of .)<br><br></li>\n",popforecast, stepm, model); */
1.222 brouard 8279: fflush(fichtm);
1.126 brouard 8280:
1.225 brouard 8281: m=pow(2,cptcoveff);
1.222 brouard 8282: if (cptcovn < 1) {m=1;ncodemax[1]=1;}
1.126 brouard 8283:
1.317 brouard 8284: fprintf(fichtm," <ul><li><b>Graphs (second order)</b></li><p>");
8285:
8286: jj1=0;
8287:
8288: fprintf(fichtm," \n<ul>");
1.337 brouard 8289: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
8290: /* k1=nres; */
1.338 brouard 8291: k1=TKresult[nres];
1.337 brouard 8292: /* for(k1=1; k1<=m;k1++){ /\* For each combination of covariate *\/ */
8293: /* if(m != 1 && TKresult[nres]!= k1) */
8294: /* continue; */
1.317 brouard 8295: jj1++;
8296: if (cptcovn > 0) {
8297: fprintf(fichtm,"\n<li><a size=\"1\" color=\"#EC5E5E\" href=\"#rescovsecond");
1.337 brouard 8298: for (cpt=1; cpt<=cptcovs;cpt++){
8299: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8300: }
8301: fprintf(fichtm,"\">");
8302:
8303: /* if(nqfveff+nqtveff 0) */ /* Test to be done */
8304: fprintf(fichtm,"************ Results for covariates");
1.337 brouard 8305: for (cpt=1; cpt<=cptcovs;cpt++){
8306: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8307: }
8308: if(invalidvarcomb[k1]){
8309: fprintf(fichtm," Warning Combination (%d) ignored because no cases ",k1);
8310: continue;
8311: }
8312: fprintf(fichtm,"</a></li>");
8313: } /* cptcovn >0 */
1.337 brouard 8314: } /* End nres */
1.317 brouard 8315: fprintf(fichtm," \n</ul>");
8316:
1.222 brouard 8317: jj1=0;
1.237 brouard 8318:
1.241 brouard 8319: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8320: /* k1=nres; */
1.338 brouard 8321: k1=TKresult[nres];
8322: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8323: /* for(k1=1; k1<=m;k1++){ */
8324: /* if(m != 1 && TKresult[nres]!= k1) */
8325: /* continue; */
1.222 brouard 8326: /* for(i1=1; i1<=ncodemax[k1];i1++){ */
8327: jj1++;
1.126 brouard 8328: if (cptcovn > 0) {
1.317 brouard 8329: fprintf(fichtm,"\n<p><a name=\"rescovsecond");
1.337 brouard 8330: for (cpt=1; cpt<=cptcovs;cpt++){
8331: fprintf(fichtm,"_V%d=%lg_",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.317 brouard 8332: }
8333: fprintf(fichtm,"\"</a>");
8334:
1.126 brouard 8335: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\">************ Results for covariates");
1.337 brouard 8336: for (cpt=1; cpt<=cptcovs;cpt++){ /**< cptcoveff number of variables */
8337: fprintf(fichtm," V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
8338: printf(" V%d=%lg ",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);
1.237 brouard 8339: /* fprintf(fichtm," V%d=%d ",Tvaraff[cpt],nbcode[Tvaraff[cpt]][codtabm(jj1,cpt)]); */
1.317 brouard 8340: }
1.237 brouard 8341:
1.338 brouard 8342: fprintf(fichtm," (model=1+age+%s) ************\n<hr size=\"2\" color=\"#EC5E5E\">",model);
1.220 brouard 8343:
1.222 brouard 8344: if(invalidvarcomb[k1]){
8345: fprintf(fichtm,"\n<h4>Combination (%d) ignored because no cases </h4>\n",k1);
8346: continue;
8347: }
1.337 brouard 8348: } /* If cptcovn >0 */
1.126 brouard 8349: for(cpt=1; cpt<=nlstate;cpt++) {
1.258 brouard 8350: fprintf(fichtm,"\n<br>- Observed (cross-sectional with mov_average=%d) and period (incidence based) \
1.314 brouard 8351: prevalence (with 95%% confidence interval) in state (%d): <a href=\"%s_%d-%d-%d.svg\"> %s_%d-%d-%d.svg</a>",mobilav,cpt,subdirf2(optionfilefiname,"V_"),cpt,k1,nres,subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
8352: fprintf(fichtm," (data from text file <a href=\"%s\">%s</a>)\n <br>",subdirf2(fileresu,"VPL_"),subdirf2(fileresu,"VPL_"));
8353: fprintf(fichtm,"<img src=\"%s_%d-%d-%d.svg\">",subdirf2(optionfilefiname,"V_"), cpt,k1,nres);
1.126 brouard 8354: }
8355: fprintf(fichtm,"\n<br>- Total life expectancy by age and \
1.314 brouard 8356: health expectancies in each live states (1 to %d). If popbased=1 the smooth (due to the model) \
1.128 brouard 8357: true period expectancies (those weighted with period prevalences are also\
8358: drawn in addition to the population based expectancies computed using\
1.314 brouard 8359: observed and cahotic prevalences: <a href=\"%s_%d-%d.svg\">%s_%d-%d.svg</a>",nlstate, subdirf2(optionfilefiname,"E_"),k1,nres,subdirf2(optionfilefiname,"E_"),k1,nres);
8360: fprintf(fichtm," (data from text file <a href=\"%s.txt\">%s.txt</a>) \n<br>",subdirf2(optionfilefiname,"T_"),subdirf2(optionfilefiname,"T_"));
8361: fprintf(fichtm,"<img src=\"%s_%d-%d.svg\">",subdirf2(optionfilefiname,"E_"),k1,nres);
1.222 brouard 8362: /* } /\* end i1 *\/ */
1.241 brouard 8363: }/* End nres */
1.222 brouard 8364: fprintf(fichtm,"</ul>");
8365: fflush(fichtm);
1.126 brouard 8366: }
8367:
8368: /******************* Gnuplot file **************/
1.296 brouard 8369: void printinggnuplot(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double bage, double fage , int prevfcast, int prevbcast, char pathc[], double p[], int offyear, int offbyear){
1.126 brouard 8370:
1.354 ! brouard 8371: char dirfileres[256],optfileres[256];
! 8372: char gplotcondition[256], gplotlabel[256];
1.343 brouard 8373: int cpt=0,k1=0,i=0,k=0,j=0,jk=0,k2=0,k3=0,k4=0,kf=0,kvar=0,kk=0,ipos=0,iposold=0,ij=0, ijp=0, l=0;
1.211 brouard 8374: int lv=0, vlv=0, kl=0;
1.130 brouard 8375: int ng=0;
1.201 brouard 8376: int vpopbased;
1.223 brouard 8377: int ioffset; /* variable offset for columns */
1.270 brouard 8378: int iyearc=1; /* variable column for year of projection */
8379: int iagec=1; /* variable column for age of projection */
1.235 brouard 8380: int nres=0; /* Index of resultline */
1.266 brouard 8381: int istart=1; /* For starting graphs in projections */
1.219 brouard 8382:
1.126 brouard 8383: /* if((ficgp=fopen(optionfilegnuplot,"a"))==NULL) { */
8384: /* printf("Problem with file %s",optionfilegnuplot); */
8385: /* fprintf(ficlog,"Problem with file %s",optionfilegnuplot); */
8386: /* } */
8387:
8388: /*#ifdef windows */
8389: fprintf(ficgp,"cd \"%s\" \n",pathc);
1.223 brouard 8390: /*#endif */
1.225 brouard 8391: m=pow(2,cptcoveff);
1.126 brouard 8392:
1.274 brouard 8393: /* diagram of the model */
8394: fprintf(ficgp,"\n#Diagram of the model \n");
8395: fprintf(ficgp,"\ndelta=0.03;delta2=0.07;unset arrow;\n");
8396: fprintf(ficgp,"yoff=(%d > 2? 0:1);\n",nlstate);
8397: fprintf(ficgp,"\n#Peripheral arrows\nset for [i=1:%d] for [j=1:%d] arrow i*10+j from cos(pi*((1-(%d/2)*2./%d)/2+(i-1)*2./%d))-(i!=j?(i-j)/abs(i-j)*delta:0), yoff +sin(pi*((1-(%d/2)*2./%d)/2+(i-1)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) rto -0.95*(cos(pi*((1-(%d/2)*2./%d)/2+(i-1)*2./%d))+(i!=j?(i-j)/abs(i-j)*delta:0) - cos(pi*((1-(%d/2)*2./%d)/2+(j-1)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta2:0)), -0.95*(sin(pi*((1-(%d/2)*2./%d)/2+(i-1)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) - sin(pi*((1-(%d/2)*2./%d)/2+(j-1)*2./%d))+( i!=j?(i-j)/abs(i-j)*delta2:0)) ls (i < j? 1:2)\n",nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate);
8398:
1.343 brouard 8399: fprintf(ficgp,"\n#Centripete arrows (turning in other direction (1-i) instead of (i-1)) \nset for [i=1:%d] for [j=1:%d] arrow (%d+1)*10+i from cos(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d))-(i!=j?(i-j)/abs(i-j)*delta:0), yoff +sin(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) rto -0.80*(cos(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d))+(i!=j?(i-j)/abs(i-j)*delta:0) ), -0.80*(sin(pi*((1-(%d/2)*2./%d)/2+(1-i)*2./%d)) + (i!=j?(i-j)/abs(i-j)*delta:0) + yoff ) ls 4\n",nlstate, nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate);
1.274 brouard 8400: fprintf(ficgp,"\n#show arrow\nunset label\n");
8401: fprintf(ficgp,"\n#States labels, starting from 2 (2-i) instead of (1-i), was (i-1)\nset for [i=1:%d] label i sprintf(\"State %%d\",i) center at cos(pi*((1-(%d/2)*2./%d)/2+(2-i)*2./%d)), yoff+sin(pi*((1-(%d/2)*2./%d)/2+(2-i)*2./%d)) font \"helvetica, 16\" tc rgbcolor \"blue\"\n",nlstate,nlstate,nlstate,nlstate,nlstate,nlstate,nlstate);
8402: fprintf(ficgp,"\nset label %d+1 sprintf(\"State %%d\",%d+1) center at 0.,0. font \"helvetica, 16\" tc rgbcolor \"red\"\n",nlstate,nlstate);
8403: fprintf(ficgp,"\n#show label\nunset border;unset xtics; unset ytics;\n");
8404: fprintf(ficgp,"\n\nset ter svg size 640, 480;set out \"%s_.svg\" \n",subdirf2(optionfilefiname,"D_"));
8405: fprintf(ficgp,"unset log y; plot [-1.2:1.2][yoff-1.2:1.2] 1/0 not; set out;reset;\n");
8406:
1.202 brouard 8407: /* Contribution to likelihood */
8408: /* Plot the probability implied in the likelihood */
1.223 brouard 8409: fprintf(ficgp,"\n# Contributions to the Likelihood, mle >=1. For mle=4 no interpolation, pure matrix products.\n#\n");
8410: fprintf(ficgp,"\n set log y; unset log x;set xlabel \"Age\"; set ylabel \"Likelihood (-2Log(L))\";");
8411: /* fprintf(ficgp,"\nset ter svg size 640, 480"); */ /* Too big for svg */
8412: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
1.204 brouard 8413: /* nice for mle=4 plot by number of matrix products.
1.202 brouard 8414: replot "rrtest1/toto.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with point lc 1 */
8415: /* replot exp(p1+p2*x)/(1+exp(p1+p2*x)+exp(p3+p4*x)+exp(p5+p6*x)) t "p12(x)" */
1.223 brouard 8416: /* fprintf(ficgp,"\nset out \"%s.svg\";",subdirf2(optionfilefiname,"ILK_")); */
8417: fprintf(ficgp,"\nset out \"%s-dest.png\";",subdirf2(optionfilefiname,"ILK_"));
8418: fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$13):6 t \"All sample, transitions colored by destination\" with dots lc variable; set out;\n",subdirf(fileresilk));
8419: fprintf(ficgp,"\nset out \"%s-ori.png\";",subdirf2(optionfilefiname,"ILK_"));
8420: fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$13):5 t \"All sample, transitions colored by origin\" with dots lc variable; set out;\n\n",subdirf(fileresilk));
8421: for (i=1; i<= nlstate ; i ++) {
8422: fprintf(ficgp,"\nset out \"%s-p%dj.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i);
8423: fprintf(ficgp,"unset log;\n# plot weighted, mean weight should have point size of 0.5\n plot \"%s\"",subdirf(fileresilk));
8424: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($12/4.):6 t \"p%d%d\" with points pointtype 7 ps variable lc variable \\\n",i,1,i,1);
8425: for (j=2; j<= nlstate+ndeath ; j ++) {
8426: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($12/4.):6 t \"p%d%d\" with points pointtype 7 ps variable lc variable ",i,j,i,j);
8427: }
8428: fprintf(ficgp,";\nset out; unset ylabel;\n");
8429: }
8430: /* unset log; plot "rrtest1_sorted_4/ILK_rrtest1_sorted_4.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with points lc variable */
8431: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8432: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8433: fprintf(ficgp,"\nset out;unset log\n");
8434: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
1.202 brouard 8435:
1.343 brouard 8436: /* Plot the probability implied in the likelihood by covariate value */
8437: fprintf(ficgp,"\nset ter pngcairo size 640, 480");
8438: /* if(debugILK==1){ */
8439: for(kf=1; kf <= ncovf; kf++){ /* For each simple dummy covariate of the model */
1.347 brouard 8440: kvar=Tvar[TvarFind[kf]]; /* variable name */
8441: /* k=18+Tvar[TvarFind[kf]];/\*offset because there are 18 columns in the ILK_ file but could be placed else where *\/ */
1.350 brouard 8442: /* k=18+kf;/\*offset because there are 18 columns in the ILK_ file *\/ */
8443: k=19+kf;/*offset because there are 19 columns in the ILK_ file */
1.343 brouard 8444: for (i=1; i<= nlstate ; i ++) {
8445: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8446: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
1.348 brouard 8447: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8448: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable \\\n",i,1,k,k,i,1,kvar);
8449: for (j=2; j<= nlstate+ndeath ; j ++) {
8450: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable ",i,j,k,k,i,j,kvar);
8451: }
8452: }else{
8453: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable \\\n",i,1,k,i,1,kvar);
8454: for (j=2; j<= nlstate+ndeath ; j ++) {
8455: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable ",i,j,k,i,j,kvar);
8456: }
1.343 brouard 8457: }
8458: fprintf(ficgp,";\nset out; unset ylabel;\n");
8459: }
8460: } /* End of each covariate dummy */
8461: for(ncovv=1, iposold=0, kk=0; ncovv <= ncovvt ; ncovv++){
8462: /* Other example V1 + V3 + V5 + age*V1 + age*V3 + age*V5 + V1*V3 + V3*V5 + V1*V5
8463: * kmodel = 1 2 3 4 5 6 7 8 9
8464: * varying 1 2 3 4 5
8465: * ncovv 1 2 3 4 5 6 7 8
8466: * TvarVV[ncovv] V3 5 1 3 3 5 1 5
8467: * TvarVVind[ncovv]=kmodel 2 3 7 7 8 8 9 9
8468: * TvarFind[kmodel] 1 0 0 0 0 0 0 0 0
8469: * kdata ncovcol=[V1 V2] nqv=0 ntv=[V3 V4] nqtv=V5
8470: * Dummy[kmodel] 0 0 1 2 2 3 1 1 1
8471: */
8472: ipos=TvarVVind[ncovv]; /* TvarVVind={2, 5, 5] gives the position in the model of the ncovv th varying covariate */
8473: kvar=TvarVV[ncovv]; /* TvarVV={3, 1, 3} gives the name of each varying covariate */
8474: /* printf("DebugILK ficgp ncovv=%d, kvar=TvarVV[ncovv]=%d, ipos=TvarVVind[ncovv]=%d, Dummy[ipos]=%d, Typevar[ipos]=%d\n", ncovv,kvar,ipos,Dummy[ipos],Typevar[ipos]); */
8475: if(ipos!=iposold){ /* Not a product or first of a product */
8476: /* printf(" %d",ipos); */
8477: /* fprintf(ficresilk," V%d",TvarVV[ncovv]); */
8478: /* printf(" DebugILK ficgp suite ipos=%d != iposold=%d\n", ipos, iposold); */
8479: kk++; /* Position of the ncovv column in ILK_ */
8480: k=18+ncovf+kk; /*offset because there are 18 columns in the ILK_ file plus ncovf fixed covariate */
8481: if(Dummy[ipos]==0 && Typevar[ipos]==0){ /* Only if dummy time varying: Dummy(0, 1=quant singor prod without age,2 dummy*age, 3quant*age) Typevar (0 single, 1=*age,2=Vn*vm) */
8482: for (i=1; i<= nlstate ; i ++) {
8483: fprintf(ficgp,"\nset out \"%s-p%dj-%d.png\";set ylabel \"Probability for each individual/wave\";",subdirf2(optionfilefiname,"ILK_"),i,kvar);
8484: fprintf(ficgp,"unset log;\n# For each simple dummy covariate of the model \n plot \"%s\"",subdirf(fileresilk));
8485:
1.348 brouard 8486: /* printf("Before DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
1.343 brouard 8487: if(gnuplotversion >=5.2){ /* Former gnuplot versions do not have variable pointsize!! */
8488: /* printf("DebugILK gnuplotversion=%g >=5.2\n",gnuplotversion); */
8489: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable \\\n",i,1,k,k,i,1,kvar);
8490: for (j=2; j<= nlstate+ndeath ; j ++) {
8491: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? 7 : 9):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt variable ps 0.4 lc variable ",i,j,k,k,i,j,kvar);
8492: }
8493: }else{
8494: /* printf("DebugILK gnuplotversion=%g <5.2\n",gnuplotversion); */
8495: fprintf(ficgp," u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable \\\n",i,1,k,i,1,kvar);
8496: for (j=2; j<= nlstate+ndeath ; j ++) {
8497: fprintf(ficgp,",\\\n \"\" u 2:($5 == %d && $6==%d ? $10 : 1/0):($%d==0 ? $6 : $6+4) t \"p%d%d V%d\" with points pt 7 ps 0.4 lc variable ",i,j,k,i,j,kvar);
8498: }
8499: }
8500: fprintf(ficgp,";\nset out; unset ylabel;\n");
8501: }
8502: }/* End if dummy varying */
8503: }else{ /*Product */
8504: /* printf("*"); */
8505: /* fprintf(ficresilk,"*"); */
8506: }
8507: iposold=ipos;
8508: } /* For each time varying covariate */
8509: /* } /\* debugILK==1 *\/ */
8510: /* unset log; plot "rrtest1_sorted_4/ILK_rrtest1_sorted_4.txt" u 2:($4 == 1 && $5==2 ? $9 : 1/0):5 t "p12" with points lc variable */
8511: /* fprintf(ficgp,"\nset log y;plot \"%s\" u 2:(-$11):3 t \"All sample, all transitions\" with dots lc variable",subdirf(fileresilk)); */
8512: /* fprintf(ficgp,"\nreplot \"%s\" u 2:($3 <= 3 ? -$11 : 1/0):3 t \"First 3 individuals\" with line lc variable", subdirf(fileresilk)); */
8513: fprintf(ficgp,"\nset out;unset log\n");
8514: /* fprintf(ficgp,"\nset out \"%s.svg\"; replot; set out; # bug gnuplot",subdirf2(optionfilefiname,"ILK_")); */
8515:
8516:
8517:
1.126 brouard 8518: strcpy(dirfileres,optionfilefiname);
8519: strcpy(optfileres,"vpl");
1.223 brouard 8520: /* 1eme*/
1.238 brouard 8521: for (cpt=1; cpt<= nlstate ; cpt ++){ /* For each live state */
1.337 brouard 8522: /* for (k1=1; k1<= m ; k1 ++){ /\* For each valid combination of covariate *\/ */
1.236 brouard 8523: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8524: k1=TKresult[nres];
1.338 brouard 8525: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.238 brouard 8526: /* plot [100000000000000000000:-100000000000000000000] "mysbiaspar/vplrmysbiaspar.txt to check */
1.337 brouard 8527: /* if(m != 1 && TKresult[nres]!= k1) */
8528: /* continue; */
1.238 brouard 8529: /* We are interested in selected combination by the resultline */
1.246 brouard 8530: /* printf("\n# 1st: Period (stable) prevalence with CI: 'VPL_' files and live state =%d ", cpt); */
1.288 brouard 8531: fprintf(ficgp,"\n# 1st: Forward (stable period) prevalence with CI: 'VPL_' files and live state =%d ", cpt);
1.264 brouard 8532: strcpy(gplotlabel,"(");
1.337 brouard 8533: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8534: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8535: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8536:
8537: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate k get corresponding value lv for combination k1 *\/ */
8538: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the value of the covariate corresponding to k1 combination *\\/ *\/ */
8539: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8540: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8541: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8542: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8543: /* vlv= nbcode[Tvaraff[k]][lv]; /\* vlv is the value of the covariate lv, 0 or 1 *\/ */
8544: /* /\* For each combination of covariate k1 (V1=1, V3=0), we printed the current covariate k and its value vlv *\/ */
8545: /* /\* printf(" V%d=%d ",Tvaraff[k],vlv); *\/ */
8546: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8547: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8548: /* } */
8549: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8550: /* /\* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); *\/ */
8551: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8552: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.264 brouard 8553: }
8554: strcpy(gplotlabel+strlen(gplotlabel),")");
1.246 brouard 8555: /* printf("\n#\n"); */
1.238 brouard 8556: fprintf(ficgp,"\n#\n");
8557: if(invalidvarcomb[k1]){
1.260 brouard 8558: /*k1=k1-1;*/ /* To be checked */
1.238 brouard 8559: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8560: continue;
8561: }
1.235 brouard 8562:
1.241 brouard 8563: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"V_"),cpt,k1,nres);
8564: fprintf(ficgp,"\n#set out \"V_%s_%d-%d-%d.svg\" \n",optionfilefiname,cpt,k1,nres);
1.276 brouard 8565: /* fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel); */
1.338 brouard 8566: fprintf(ficgp,"set title \"Alive state %d %s model=1+age+%s\" font \"Helvetica,12\"\n",cpt,gplotlabel,model);
1.260 brouard 8567: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nset ter svg size 640, 480\nplot [%.f:%.f] \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",ageminpar,fage,subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
8568: /* fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \nset ter svg size 640, 480\nplot [%.f:%.f] \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",ageminpar,fage,subdirf2(fileresu,"VPL_"),k1-1,k1-1,nres); */
8569: /* k1-1 error should be nres-1*/
1.238 brouard 8570: for (i=1; i<= nlstate ; i ++) {
8571: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8572: else fprintf(ficgp," %%*lf (%%*lf)");
8573: }
1.288 brouard 8574: fprintf(ficgp,"\" t\"Forward prevalence\" w l lt 0,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 8575: for (i=1; i<= nlstate ; i ++) {
8576: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8577: else fprintf(ficgp," %%*lf (%%*lf)");
8578: }
1.260 brouard 8579: fprintf(ficgp,"\" t\"95%% CI\" w l lt 1,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VPL_"),nres-1,nres-1,nres);
1.238 brouard 8580: for (i=1; i<= nlstate ; i ++) {
8581: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8582: else fprintf(ficgp," %%*lf (%%*lf)");
8583: }
1.265 brouard 8584: /* fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" every :::%d::%d u 1:($%d) t\"Observed prevalence\" w l lt 2",subdirf2(fileresu,"P_"),k1-1,k1-1,2+4*(cpt-1)); */
8585:
8586: fprintf(ficgp,"\" t\"\" w l lt 1,\"%s\" u 1:((",subdirf2(fileresu,"P_"));
8587: if(cptcoveff ==0){
1.271 brouard 8588: fprintf(ficgp,"$%d)) t 'Observed prevalence in state %d' with line lt 3", 2+3*(cpt-1), cpt );
1.265 brouard 8589: }else{
8590: kl=0;
8591: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8592: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8593: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.265 brouard 8594: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8595: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8596: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
8597: vlv= nbcode[Tvaraff[k]][lv];
8598: kl++;
8599: /* kl=6+(cpt-1)*(nlstate+1)+1+(i-1); /\* 6+(1-1)*(2+1)+1+(1-1)=7, 6+(2-1)(2+1)+1+(1-1)=10 *\/ */
8600: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8601: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8602: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8603: if(k==cptcoveff){
8604: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Observed prevalence in state %d' w l lt 2",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
8605: 2+cptcoveff*2+3*(cpt-1), cpt ); /* 4 or 6 ?*/
8606: }else{
8607: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv]);
8608: kl++;
8609: }
8610: } /* end covariate */
8611: } /* end if no covariate */
8612:
1.296 brouard 8613: if(prevbcast==1){ /* We need to get the corresponding values of the covariates involved in this combination k1 */
1.238 brouard 8614: /* fprintf(ficgp,",\"%s\" every :::%d::%d u 1:($%d) t\"Backward stable prevalence\" w l lt 3",subdirf2(fileresu,"PLB_"),k1-1,k1-1,1+cpt); */
1.242 brouard 8615: fprintf(ficgp,",\"%s\" u 1:((",subdirf2(fileresu,"PLB_")); /* Age is in 1, nres in 2 to be fixed */
1.238 brouard 8616: if(cptcoveff ==0){
1.245 brouard 8617: fprintf(ficgp,"$%d)) t 'Backward prevalence in state %d' with line lt 3", 2+(cpt-1), cpt );
1.238 brouard 8618: }else{
8619: kl=0;
8620: for (k=1; k<=cptcoveff; k++){ /* For each combination of covariate */
1.332 brouard 8621: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to k1 combination and kth covariate *\/ */
8622: lv=codtabm(k1,TnsdVar[Tvaraff[k]]);
1.238 brouard 8623: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
8624: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
8625: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 8626: /* vlv= nbcode[Tvaraff[k]][lv]; */
8627: vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])];
1.223 brouard 8628: kl++;
1.238 brouard 8629: /* kl=6+(cpt-1)*(nlstate+1)+1+(i-1); /\* 6+(1-1)*(2+1)+1+(1-1)=7, 6+(2-1)(2+1)+1+(1-1)=10 *\/ */
8630: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
8631: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
8632: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
8633: if(k==cptcoveff){
1.245 brouard 8634: fprintf(ficgp,"$%d==%d && $%d==%d)? $%d : 1/0) t 'Backward prevalence in state %d' w l lt 3",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][lv], \
1.242 brouard 8635: 2+cptcoveff*2+(cpt-1), cpt ); /* 4 or 6 ?*/
1.238 brouard 8636: }else{
1.332 brouard 8637: fprintf(ficgp,"$%d==%d && $%d==%d && ",kl+1, Tvaraff[k],kl+1+1,nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]);
1.238 brouard 8638: kl++;
8639: }
8640: } /* end covariate */
8641: } /* end if no covariate */
1.296 brouard 8642: if(prevbcast == 1){
1.268 brouard 8643: fprintf(ficgp,", \"%s\" every :::%d::%d u 1:($2==%d ? $3:1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
8644: /* k1-1 error should be nres-1*/
8645: for (i=1; i<= nlstate ; i ++) {
8646: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8647: else fprintf(ficgp," %%*lf (%%*lf)");
8648: }
1.271 brouard 8649: fprintf(ficgp,"\" t\"Backward (stable) prevalence\" w l lt 6 dt 3,\"%s\" every :::%d::%d u 1:($2==%d ? $3+1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
1.268 brouard 8650: for (i=1; i<= nlstate ; i ++) {
8651: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8652: else fprintf(ficgp," %%*lf (%%*lf)");
8653: }
1.276 brouard 8654: fprintf(ficgp,"\" t\"95%% CI\" w l lt 4,\"%s\" every :::%d::%d u 1:($2==%d ? $3-1.96*$4 : 1/0) \"%%lf %%lf",subdirf2(fileresu,"VBL_"),nres-1,nres-1,nres);
1.268 brouard 8655: for (i=1; i<= nlstate ; i ++) {
8656: if (i==cpt) fprintf(ficgp," %%lf (%%lf)");
8657: else fprintf(ficgp," %%*lf (%%*lf)");
8658: }
1.274 brouard 8659: fprintf(ficgp,"\" t\"\" w l lt 4");
1.268 brouard 8660: } /* end if backprojcast */
1.296 brouard 8661: } /* end if prevbcast */
1.276 brouard 8662: /* fprintf(ficgp,"\nset out ;unset label;\n"); */
8663: fprintf(ficgp,"\nset out ;unset title;\n");
1.238 brouard 8664: } /* nres */
1.337 brouard 8665: /* } /\* k1 *\/ */
1.201 brouard 8666: } /* cpt */
1.235 brouard 8667:
8668:
1.126 brouard 8669: /*2 eme*/
1.337 brouard 8670: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8671: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8672: k1=TKresult[nres];
1.338 brouard 8673: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8674: /* if(m != 1 && TKresult[nres]!= k1) */
8675: /* continue; */
1.238 brouard 8676: fprintf(ficgp,"\n# 2nd: Total life expectancy with CI: 't' files ");
1.264 brouard 8677: strcpy(gplotlabel,"(");
1.337 brouard 8678: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8679: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8680: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8681: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8682: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8683: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8684: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8685: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8686: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8687: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8688: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8689: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8690: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8691: /* } */
8692: /* /\* for(k=1; k <= ncovds; k++){ *\/ */
8693: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8694: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8695: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
8696: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
1.238 brouard 8697: }
1.264 brouard 8698: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8699: fprintf(ficgp,"\n#\n");
1.223 brouard 8700: if(invalidvarcomb[k1]){
8701: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8702: continue;
8703: }
1.219 brouard 8704:
1.241 brouard 8705: fprintf(ficgp,"\nset out \"%s_%d-%d.svg\" \n",subdirf2(optionfilefiname,"E_"),k1,nres);
1.238 brouard 8706: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.264 brouard 8707: fprintf(ficgp,"\nset label \"popbased %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",vpopbased,gplotlabel);
8708: if(vpopbased==0){
1.238 brouard 8709: fprintf(ficgp,"set ylabel \"Years\" \nset ter svg size 640, 480\nplot [%.f:%.f] ",ageminpar,fage);
1.264 brouard 8710: }else
1.238 brouard 8711: fprintf(ficgp,"\nreplot ");
8712: for (i=1; i<= nlstate+1 ; i ++) {
8713: k=2*i;
1.261 brouard 8714: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ?$4 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1, vpopbased);
1.238 brouard 8715: for (j=1; j<= nlstate+1 ; j ++) {
8716: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8717: else fprintf(ficgp," %%*lf (%%*lf)");
8718: }
8719: if (i== 1) fprintf(ficgp,"\" t\"TLE\" w l lt %d, \\\n",i);
8720: else fprintf(ficgp,"\" t\"LE in state (%d)\" w l lt %d, \\\n",i-1,i+1);
1.261 brouard 8721: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ? $4-$5*2 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1,vpopbased);
1.238 brouard 8722: for (j=1; j<= nlstate+1 ; j ++) {
8723: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8724: else fprintf(ficgp," %%*lf (%%*lf)");
8725: }
8726: fprintf(ficgp,"\" t\"\" w l lt 0,");
1.261 brouard 8727: fprintf(ficgp,"\"%s\" every :::%d::%d u 1:($2==%d && $4!=0 ? $4+$5*2 : 1/0) \"%%lf %%lf %%lf",subdirf2(fileresu,"T_"),nres-1,nres-1,vpopbased);
1.238 brouard 8728: for (j=1; j<= nlstate+1 ; j ++) {
8729: if (j==i) fprintf(ficgp," %%lf (%%lf)");
8730: else fprintf(ficgp," %%*lf (%%*lf)");
8731: }
8732: if (i== (nlstate+1)) fprintf(ficgp,"\" t\"\" w l lt 0");
8733: else fprintf(ficgp,"\" t\"\" w l lt 0,\\\n");
8734: } /* state */
8735: } /* vpopbased */
1.264 brouard 8736: fprintf(ficgp,"\nset out;set out \"%s_%d-%d.svg\"; replot; set out; unset label;\n",subdirf2(optionfilefiname,"E_"),k1,nres); /* Buggy gnuplot */
1.238 brouard 8737: } /* end nres */
1.337 brouard 8738: /* } /\* k1 end 2 eme*\/ */
1.238 brouard 8739:
8740:
8741: /*3eme*/
1.337 brouard 8742: /* for (k1=1; k1<= m ; k1 ++){ */
1.238 brouard 8743: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8744: k1=TKresult[nres];
1.338 brouard 8745: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8746: /* if(m != 1 && TKresult[nres]!= k1) */
8747: /* continue; */
1.238 brouard 8748:
1.332 brouard 8749: for (cpt=1; cpt<= nlstate ; cpt ++) { /* Fragile no verification of covariate values */
1.261 brouard 8750: fprintf(ficgp,"\n\n# 3d: Life expectancy with EXP_ files: combination=%d state=%d",k1, cpt);
1.264 brouard 8751: strcpy(gplotlabel,"(");
1.337 brouard 8752: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8753: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8754: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8755: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8756: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8757: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
8758: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8759: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8760: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8761: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8762: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8763: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8764: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8765: /* } */
8766: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8767: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8768: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][resultmodel[nres][k4]]); */
8769: }
1.264 brouard 8770: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8771: fprintf(ficgp,"\n#\n");
8772: if(invalidvarcomb[k1]){
8773: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8774: continue;
8775: }
8776:
8777: /* k=2+nlstate*(2*cpt-2); */
8778: k=2+(nlstate+1)*(cpt-1);
1.241 brouard 8779: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"EXP_"),cpt,k1,nres);
1.264 brouard 8780: fprintf(ficgp,"set label \"%s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel);
1.238 brouard 8781: fprintf(ficgp,"set ter svg size 640, 480\n\
1.261 brouard 8782: plot [%.f:%.f] \"%s\" every :::%d::%d u 1:%d t \"e%d1\" w l",ageminpar,fage,subdirf2(fileresu,"E_"),nres-1,nres-1,k,cpt);
1.238 brouard 8783: /*fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d-2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8784: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8785: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
8786: fprintf(ficgp,",\"e%s\" every :::%d::%d u 1:($%d+2*$%d) \"\%%lf ",fileres,k1-1,k1-1,k,k+1);
8787: for (i=1; i<= nlstate*2 ; i ++) fprintf(ficgp,"\%%lf (\%%lf) ");
8788: fprintf(ficgp,"\" t \"e%d1\" w l",cpt);
1.219 brouard 8789:
1.238 brouard 8790: */
8791: for (i=1; i< nlstate ; i ++) {
1.261 brouard 8792: fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d%d\" w l",subdirf2(fileresu,"E_"),nres-1,nres-1,k+i,cpt,i+1);
1.238 brouard 8793: /* fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d%d\" w l",subdirf2(fileres,"e"),k1-1,k1-1,k+2*i,cpt,i+1);*/
1.219 brouard 8794:
1.238 brouard 8795: }
1.261 brouard 8796: fprintf(ficgp," ,\"%s\" every :::%d::%d u 1:%d t \"e%d.\" w l",subdirf2(fileresu,"E_"),nres-1,nres-1,k+nlstate,cpt);
1.238 brouard 8797: }
1.264 brouard 8798: fprintf(ficgp,"\nunset label;\n");
1.238 brouard 8799: } /* end nres */
1.337 brouard 8800: /* } /\* end kl 3eme *\/ */
1.126 brouard 8801:
1.223 brouard 8802: /* 4eme */
1.201 brouard 8803: /* Survival functions (period) from state i in state j by initial state i */
1.337 brouard 8804: /* for (k1=1; k1<=m; k1++){ /\* For each covariate and each value *\/ */
1.238 brouard 8805: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8806: k1=TKresult[nres];
1.338 brouard 8807: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8808: /* if(m != 1 && TKresult[nres]!= k1) */
8809: /* continue; */
1.238 brouard 8810: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state cpt*/
1.264 brouard 8811: strcpy(gplotlabel,"(");
1.337 brouard 8812: fprintf(ficgp,"\n#\n#\n# Survival functions in state %d : 'LIJ_' files, cov=%d state=%d", cpt, k1, cpt);
8813: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8814: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8815: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8816: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8817: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8818: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8819: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8820: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8821: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8822: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8823: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8824: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8825: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8826: /* } */
8827: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8828: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8829: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8830: }
1.264 brouard 8831: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8832: fprintf(ficgp,"\n#\n");
8833: if(invalidvarcomb[k1]){
8834: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8835: continue;
1.223 brouard 8836: }
1.238 brouard 8837:
1.241 brouard 8838: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJ_"),cpt,k1,nres);
1.264 brouard 8839: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.238 brouard 8840: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8841: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8842: k=3;
8843: for (i=1; i<= nlstate ; i ++){
8844: if(i==1){
8845: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8846: }else{
8847: fprintf(ficgp,", '' ");
8848: }
8849: l=(nlstate+ndeath)*(i-1)+1;
8850: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8851: for (j=2; j<= nlstate+ndeath ; j ++)
8852: fprintf(ficgp,"+$%d",k+l+j-1);
8853: fprintf(ficgp,")) t \"l(%d,%d)\" w l",i,cpt);
8854: } /* nlstate */
1.264 brouard 8855: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8856: } /* end cpt state*/
8857: } /* end nres */
1.337 brouard 8858: /* } /\* end covariate k1 *\/ */
1.238 brouard 8859:
1.220 brouard 8860: /* 5eme */
1.201 brouard 8861: /* Survival functions (period) from state i in state j by final state j */
1.337 brouard 8862: /* for (k1=1; k1<= m ; k1++){ /\* For each covariate combination if any *\/ */
1.238 brouard 8863: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8864: k1=TKresult[nres];
1.338 brouard 8865: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8866: /* if(m != 1 && TKresult[nres]!= k1) */
8867: /* continue; */
1.238 brouard 8868: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each inital state */
1.264 brouard 8869: strcpy(gplotlabel,"(");
1.238 brouard 8870: fprintf(ficgp,"\n#\n#\n# Survival functions in state j and all livestates from state i by final state j: 'lij' files, cov=%d state=%d",k1, cpt);
1.337 brouard 8871: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8872: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8873: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8874: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8875: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8876: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8877: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8878: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8879: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8880: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8881: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8882: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8883: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8884: /* } */
8885: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8886: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8887: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.238 brouard 8888: }
1.264 brouard 8889: strcpy(gplotlabel+strlen(gplotlabel),")");
1.238 brouard 8890: fprintf(ficgp,"\n#\n");
8891: if(invalidvarcomb[k1]){
8892: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8893: continue;
8894: }
1.227 brouard 8895:
1.241 brouard 8896: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"LIJT_"),cpt,k1,nres);
1.264 brouard 8897: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.238 brouard 8898: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability to be alive\" \n\
8899: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
8900: k=3;
8901: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8902: if(j==1)
8903: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8904: else
8905: fprintf(ficgp,", '' ");
8906: l=(nlstate+ndeath)*(cpt-1) +j;
8907: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):($%d",k1,k+l);
8908: /* for (i=2; i<= nlstate+ndeath ; i ++) */
8909: /* fprintf(ficgp,"+$%d",k+l+i-1); */
8910: fprintf(ficgp,") t \"l(%d,%d)\" w l",cpt,j);
8911: } /* nlstate */
8912: fprintf(ficgp,", '' ");
8913: fprintf(ficgp," u (($1==%d && (floor($2)%%5 == 0)) ? ($3):1/0):(",k1);
8914: for (j=1; j<= nlstate ; j ++){ /* Lived in state j */
8915: l=(nlstate+ndeath)*(cpt-1) +j;
8916: if(j < nlstate)
8917: fprintf(ficgp,"$%d +",k+l);
8918: else
8919: fprintf(ficgp,"$%d) t\"l(%d,.)\" w l",k+l,cpt);
8920: }
1.264 brouard 8921: fprintf(ficgp,"\nset out; unset label;\n");
1.238 brouard 8922: } /* end cpt state*/
1.337 brouard 8923: /* } /\* end covariate *\/ */
1.238 brouard 8924: } /* end nres */
1.227 brouard 8925:
1.220 brouard 8926: /* 6eme */
1.202 brouard 8927: /* CV preval stable (period) for each covariate */
1.337 brouard 8928: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8929: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8930: k1=TKresult[nres];
1.338 brouard 8931: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8932: /* if(m != 1 && TKresult[nres]!= k1) */
8933: /* continue; */
1.255 brouard 8934: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state of arrival */
1.264 brouard 8935: strcpy(gplotlabel,"(");
1.288 brouard 8936: fprintf(ficgp,"\n#\n#\n#CV preval stable (forward): 'pij' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8937: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8938: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8939: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8940: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8941: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
8942: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
8943: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
8944: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
8945: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
8946: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
8947: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
8948: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
8949: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
8950: /* } */
8951: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
8952: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
8953: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 8954: }
1.264 brouard 8955: strcpy(gplotlabel+strlen(gplotlabel),")");
1.211 brouard 8956: fprintf(ficgp,"\n#\n");
1.223 brouard 8957: if(invalidvarcomb[k1]){
1.227 brouard 8958: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
8959: continue;
1.223 brouard 8960: }
1.227 brouard 8961:
1.241 brouard 8962: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"P_"),cpt,k1,nres);
1.264 brouard 8963: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.126 brouard 8964: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 8965: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.211 brouard 8966: k=3; /* Offset */
1.255 brouard 8967: for (i=1; i<= nlstate ; i ++){ /* State of origin */
1.227 brouard 8968: if(i==1)
8969: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJ_"));
8970: else
8971: fprintf(ficgp,", '' ");
1.255 brouard 8972: l=(nlstate+ndeath)*(i-1)+1; /* 1, 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.227 brouard 8973: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l);
8974: for (j=2; j<= nlstate ; j ++)
8975: fprintf(ficgp,"+$%d",k+l+j-1);
8976: fprintf(ficgp,")) t \"prev(%d,%d)\" w l",i,cpt);
1.153 brouard 8977: } /* nlstate */
1.264 brouard 8978: fprintf(ficgp,"\nset out; unset label;\n");
1.153 brouard 8979: } /* end cpt state*/
8980: } /* end covariate */
1.227 brouard 8981:
8982:
1.220 brouard 8983: /* 7eme */
1.296 brouard 8984: if(prevbcast == 1){
1.288 brouard 8985: /* CV backward prevalence for each covariate */
1.337 brouard 8986: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 8987: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 8988: k1=TKresult[nres];
1.338 brouard 8989: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 8990: /* if(m != 1 && TKresult[nres]!= k1) */
8991: /* continue; */
1.268 brouard 8992: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life origin state */
1.264 brouard 8993: strcpy(gplotlabel,"(");
1.288 brouard 8994: fprintf(ficgp,"\n#\n#\n#CV Backward stable prevalence: 'pijb' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 8995: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
8996: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8997: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
8998: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate and each value *\/ */
8999: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate number corresponding to k1 combination *\\/ *\/ */
9000: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9001: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9002: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9003: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9004: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9005: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9006: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9007: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9008: /* } */
9009: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9010: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9011: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 9012: }
1.264 brouard 9013: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9014: fprintf(ficgp,"\n#\n");
9015: if(invalidvarcomb[k1]){
9016: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9017: continue;
9018: }
9019:
1.241 brouard 9020: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PB_"),cpt,k1,nres);
1.268 brouard 9021: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.227 brouard 9022: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Probability\" \n\
1.238 brouard 9023: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.227 brouard 9024: k=3; /* Offset */
1.268 brouard 9025: for (i=1; i<= nlstate ; i ++){ /* State of arrival */
1.227 brouard 9026: if(i==1)
9027: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"PIJB_"));
9028: else
9029: fprintf(ficgp,", '' ");
9030: /* l=(nlstate+ndeath)*(i-1)+1; */
1.255 brouard 9031: l=(nlstate+ndeath)*(cpt-1)+1; /* fixed for i; cpt=1 1, cpt=2 1+ nlstate+ndeath, 1+2*(nlstate+ndeath) */
1.324 brouard 9032: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l); /\* a vérifier *\/ */
9033: /* fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d/($%d",k1,k+l+(cpt-1),k+l+(cpt-1)+i-1); /\* a vérifier *\/ */
1.255 brouard 9034: fprintf(ficgp," u ($1==%d ? ($3):1/0):($%d",k1,k+l+i-1); /* To be verified */
1.227 brouard 9035: /* for (j=2; j<= nlstate ; j ++) */
9036: /* fprintf(ficgp,"+$%d",k+l+j-1); */
9037: /* /\* fprintf(ficgp,"+$%d",k+l+j-1); *\/ */
1.268 brouard 9038: fprintf(ficgp,") t \"bprev(%d,%d)\" w l",cpt,i);
1.227 brouard 9039: } /* nlstate */
1.264 brouard 9040: fprintf(ficgp,"\nset out; unset label;\n");
1.218 brouard 9041: } /* end cpt state*/
9042: } /* end covariate */
1.296 brouard 9043: } /* End if prevbcast */
1.218 brouard 9044:
1.223 brouard 9045: /* 8eme */
1.218 brouard 9046: if(prevfcast==1){
1.288 brouard 9047: /* Projection from cross-sectional to forward stable (period) prevalence for each covariate */
1.218 brouard 9048:
1.337 brouard 9049: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.237 brouard 9050: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9051: k1=TKresult[nres];
1.338 brouard 9052: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9053: /* if(m != 1 && TKresult[nres]!= k1) */
9054: /* continue; */
1.211 brouard 9055: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
1.264 brouard 9056: strcpy(gplotlabel,"(");
1.288 brouard 9057: fprintf(ficgp,"\n#\n#\n#Projection of prevalence to forward stable prevalence (period): 'PROJ_' files, covariatecombination#=%d state=%d",k1, cpt);
1.337 brouard 9058: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9059: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9060: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9061: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9062: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9063: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9064: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9065: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9066: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9067: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9068: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9069: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9070: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9071: /* } */
9072: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9073: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9074: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.237 brouard 9075: }
1.264 brouard 9076: strcpy(gplotlabel+strlen(gplotlabel),")");
1.227 brouard 9077: fprintf(ficgp,"\n#\n");
9078: if(invalidvarcomb[k1]){
9079: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9080: continue;
9081: }
9082:
9083: fprintf(ficgp,"# hpijx=probability over h years, hp.jx is weighted by observed prev\n ");
1.241 brouard 9084: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJ_"),cpt,k1,nres);
1.264 brouard 9085: fprintf(ficgp,"set label \"Alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
1.227 brouard 9086: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
1.238 brouard 9087: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
1.266 brouard 9088:
9089: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9090: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9091: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9092: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
1.227 brouard 9093: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9094: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9095: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9096: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
1.266 brouard 9097: if(i==istart){
1.227 brouard 9098: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"F_"));
9099: }else{
9100: fprintf(ficgp,",\\\n '' ");
9101: }
9102: if(cptcoveff ==0){ /* No covariate */
9103: ioffset=2; /* Age is in 2 */
9104: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9105: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9106: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9107: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9108: fprintf(ficgp," u %d:(", ioffset);
1.266 brouard 9109: if(i==nlstate+1){
1.270 brouard 9110: fprintf(ficgp," $%d/(1.-$%d)):1 t 'pw.%d' with line lc variable ", \
1.266 brouard 9111: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9112: fprintf(ficgp,",\\\n '' ");
9113: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9114: fprintf(ficgp," (($1-$2) == %d ) ? $%d/(1.-$%d) : 1/0):1 with labels center not ", \
1.266 brouard 9115: offyear, \
1.268 brouard 9116: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate );
1.266 brouard 9117: }else
1.227 brouard 9118: fprintf(ficgp," $%d/(1.-$%d)) t 'p%d%d' with line ", \
9119: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9120: }else{ /* more than 2 covariates */
1.270 brouard 9121: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9122: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9123: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9124: iyearc=ioffset-1;
9125: iagec=ioffset;
1.227 brouard 9126: fprintf(ficgp," u %d:(",ioffset);
9127: kl=0;
9128: strcpy(gplotcondition,"(");
1.351 brouard 9129: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
1.332 brouard 9130: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
1.351 brouard 9131: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9132: /* lv=codtabm(k1,TnsdVar[Tvaraff[k]]); */
9133: lv=Tvresult[nres][k];
9134: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
1.227 brouard 9135: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9136: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9137: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
1.332 brouard 9138: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
1.351 brouard 9139: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
1.227 brouard 9140: kl++;
1.351 brouard 9141: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9142: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,lv, kl+1, vlv );
1.227 brouard 9143: kl++;
1.351 brouard 9144: if(k <cptcovs && cptcovs>1)
1.227 brouard 9145: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9146: }
9147: strcpy(gplotcondition+strlen(gplotcondition),")");
9148: /* kl=6+(cpt-1)*(nlstate+1)+1+(i-1); /\* 6+(1-1)*(2+1)+1+(1-1)=7, 6+(2-1)(2+1)+1+(1-1)=10 *\/ */
9149: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9150: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9151: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
9152: if(i==nlstate+1){
1.270 brouard 9153: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0):%d t 'p.%d' with line lc variable", gplotcondition, \
9154: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,iyearc, cpt );
1.266 brouard 9155: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9156: fprintf(ficgp," u %d:(",iagec);
9157: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d/(1.-$%d) : 1/0):%d with labels center not ", gplotcondition, \
9158: iyearc, iagec, offyear, \
9159: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate, iyearc );
1.266 brouard 9160: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
1.227 brouard 9161: }else{
9162: fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \
9163: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset +1+(i-1)+(nlstate+1)*nlstate,i,cpt );
9164: }
9165: } /* end if covariate */
9166: } /* nlstate */
1.264 brouard 9167: fprintf(ficgp,"\nset out; unset label;\n");
1.223 brouard 9168: } /* end cpt state*/
9169: } /* end covariate */
9170: } /* End if prevfcast */
1.227 brouard 9171:
1.296 brouard 9172: if(prevbcast==1){
1.268 brouard 9173: /* Back projection from cross-sectional to stable (mixed) for each covariate */
9174:
1.337 brouard 9175: /* for (k1=1; k1<= m ; k1 ++) /\* For each covariate combination if any *\/ */
1.268 brouard 9176: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9177: k1=TKresult[nres];
1.338 brouard 9178: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9179: /* if(m != 1 && TKresult[nres]!= k1) */
9180: /* continue; */
1.268 brouard 9181: for (cpt=1; cpt<=nlstate ; cpt ++) { /* For each life state */
9182: strcpy(gplotlabel,"(");
9183: fprintf(ficgp,"\n#\n#\n#Back projection of prevalence to stable (mixed) back prevalence: 'BPROJ_' files, covariatecombination#=%d originstate=%d",k1, cpt);
1.337 brouard 9184: for (k=1; k<=cptcovs; k++){ /* For each covariate k get corresponding value lv for combination k1 */
9185: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9186: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9187: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9188: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9189: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9190: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9191: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9192: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9193: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9194: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9195: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9196: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9197: /* } */
9198: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9199: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9200: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
1.268 brouard 9201: }
9202: strcpy(gplotlabel+strlen(gplotlabel),")");
9203: fprintf(ficgp,"\n#\n");
9204: if(invalidvarcomb[k1]){
9205: fprintf(ficgp,"#Combination (%d) ignored because no cases \n",k1);
9206: continue;
9207: }
9208:
9209: fprintf(ficgp,"# hbijx=backprobability over h years, hb.jx is weighted by observed prev at destination state\n ");
9210: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" \n",subdirf2(optionfilefiname,"PROJB_"),cpt,k1,nres);
9211: fprintf(ficgp,"set label \"Origin alive state %d %s\" at graph 0.98,0.5 center rotate font \"Helvetica,12\"\n",cpt,gplotlabel);
9212: fprintf(ficgp,"set xlabel \"Age\" \nset ylabel \"Prevalence\" \n\
9213: set ter svg size 640, 480\nunset log y\nplot [%.f:%.f] ", ageminpar, agemaxpar);
9214:
9215: /* for (i=1; i<= nlstate+1 ; i ++){ /\* nlstate +1 p11 p21 p.1 *\/ */
9216: istart=nlstate+1; /* Could be one if by state, but nlstate+1 is w.i projection only */
9217: /*istart=1;*/ /* Could be one if by state, but nlstate+1 is w.i projection only */
9218: for (i=istart; i<= nlstate+1 ; i ++){ /* nlstate +1 p11 p21 p.1 */
9219: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9220: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9221: /*# yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9222: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9223: if(i==istart){
9224: fprintf(ficgp,"\"%s\"",subdirf2(fileresu,"FB_"));
9225: }else{
9226: fprintf(ficgp,",\\\n '' ");
9227: }
1.351 brouard 9228: /* if(cptcoveff ==0){ /\* No covariate *\/ */
9229: if(cptcovs ==0){ /* No covariate */
1.268 brouard 9230: ioffset=2; /* Age is in 2 */
9231: /*# yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9232: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9233: /*# V1 = 1 yearproj age p11 p21 p31 p.1 p12 p22 p32 p.2 p13 p23 p33 p.3 p14 p24 p34 p.4*/
9234: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 */
9235: fprintf(ficgp," u %d:(", ioffset);
9236: if(i==nlstate+1){
1.270 brouard 9237: fprintf(ficgp," $%d/(1.-$%d)):1 t 'bw%d' with line lc variable ", \
1.268 brouard 9238: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt );
9239: fprintf(ficgp,",\\\n '' ");
9240: fprintf(ficgp," u %d:(",ioffset);
1.270 brouard 9241: fprintf(ficgp," (($1-$2) == %d ) ? $%d : 1/0):1 with labels center not ", \
1.268 brouard 9242: offbyear, \
9243: ioffset+(cpt-1)*(nlstate+1)+1+(i-1) );
9244: }else
9245: fprintf(ficgp," $%d/(1.-$%d)) t 'b%d%d' with line ", \
9246: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), ioffset+1+(i-1)+(nlstate+1)*nlstate,cpt,i );
9247: }else{ /* more than 2 covariates */
1.270 brouard 9248: ioffset=2*cptcoveff+2; /* Age is in 4 or 6 or etc.*/
9249: /*# V1 = 1 V2 = 0 yearproj age p11 p21 p.1 p12 p22 p.2 p13 p23 p.3*/
9250: /*# 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 */
9251: iyearc=ioffset-1;
9252: iagec=ioffset;
1.268 brouard 9253: fprintf(ficgp," u %d:(",ioffset);
9254: kl=0;
9255: strcpy(gplotcondition,"(");
1.337 brouard 9256: for (k=1; k<=cptcovs; k++){ /* For each covariate k of the resultline, get corresponding value lv for combination k1 */
1.338 brouard 9257: if(Dummy[modelresult[nres][k]]==0){ /* To be verified */
1.337 brouard 9258: /* for (k=1; k<=cptcoveff; k++){ /\* For each covariate writing the chain of conditions *\/ */
9259: /* lv= decodtabm(k1,k,cptcoveff); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9260: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9261: lv=Tvresult[nres][k];
9262: vlv=TinvDoQresult[nres][Tvresult[nres][k]];
9263: /* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 */
9264: /* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 */
9265: /* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 */
9266: /* vlv= nbcode[Tvaraff[k]][lv]; /\* Value of the modality of Tvaraff[k] *\/ */
9267: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9268: kl++;
9269: /* sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%d " ,kl,Tvaraff[k], kl+1, nbcode[Tvaraff[k]][lv]); */
9270: sprintf(gplotcondition+strlen(gplotcondition),"$%d==%d && $%d==%lg " ,kl,Tvresult[nres][k], kl+1,TinvDoQresult[nres][Tvresult[nres][k]]);
9271: kl++;
1.338 brouard 9272: if(k <cptcovs && cptcovs>1)
1.337 brouard 9273: sprintf(gplotcondition+strlen(gplotcondition)," && ");
9274: }
1.268 brouard 9275: }
9276: strcpy(gplotcondition+strlen(gplotcondition),")");
9277: /* kl=6+(cpt-1)*(nlstate+1)+1+(i-1); /\* 6+(1-1)*(2+1)+1+(1-1)=7, 6+(2-1)(2+1)+1+(1-1)=10 *\/ */
9278: /*6+(cpt-1)*(nlstate+1)+1+(i-1)+(nlstate+1)*nlstate; 6+(1-1)*(2+1)+1+(1-1) +(2+1)*2=13 */
9279: /*6+1+(i-1)+(nlstate+1)*nlstate; 6+1+(1-1) +(2+1)*2=13 */
9280: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0)? $9/(1.-$15) : 1/0):($5==2000? 3:2) t 'p.1' with line lc variable*/
9281: if(i==nlstate+1){
1.270 brouard 9282: fprintf(ficgp,"%s ? $%d : 1/0):%d t 'bw%d' with line lc variable", gplotcondition, \
9283: ioffset+(cpt-1)*(nlstate+1)+1+(i-1),iyearc,cpt );
1.268 brouard 9284: fprintf(ficgp,",\\\n '' ");
1.270 brouard 9285: fprintf(ficgp," u %d:(",iagec);
1.268 brouard 9286: /* fprintf(ficgp,"%s && (($5-$6) == %d ) ? $%d/(1.-$%d) : 1/0):5 with labels center not ", gplotcondition, \ */
1.270 brouard 9287: fprintf(ficgp,"%s && (($%d-$%d) == %d ) ? $%d : 1/0):%d with labels center not ", gplotcondition, \
9288: iyearc,iagec,offbyear, \
9289: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), iyearc );
1.268 brouard 9290: /* '' u 6:(($1==1 && $2==0 && $3==2 && $4==0) && (($5-$6) == 1947) ? $10/(1.-$22) : 1/0):5 with labels center boxed not*/
9291: }else{
9292: /* fprintf(ficgp,"%s ? $%d/(1.-$%d) : 1/0) t 'p%d%d' with line ", gplotcondition, \ */
9293: fprintf(ficgp,"%s ? $%d : 1/0) t 'b%d%d' with line ", gplotcondition, \
9294: ioffset+(cpt-1)*(nlstate+1)+1+(i-1), cpt,i );
9295: }
9296: } /* end if covariate */
9297: } /* nlstate */
9298: fprintf(ficgp,"\nset out; unset label;\n");
9299: } /* end cpt state*/
9300: } /* end covariate */
1.296 brouard 9301: } /* End if prevbcast */
1.268 brouard 9302:
1.227 brouard 9303:
1.238 brouard 9304: /* 9eme writing MLE parameters */
9305: fprintf(ficgp,"\n##############\n#9eme MLE estimated parameters\n#############\n");
1.126 brouard 9306: for(i=1,jk=1; i <=nlstate; i++){
1.187 brouard 9307: fprintf(ficgp,"# initial state %d\n",i);
1.126 brouard 9308: for(k=1; k <=(nlstate+ndeath); k++){
9309: if (k != i) {
1.227 brouard 9310: fprintf(ficgp,"# current state %d\n",k);
9311: for(j=1; j <=ncovmodel; j++){
9312: fprintf(ficgp,"p%d=%f; ",jk,p[jk]);
9313: jk++;
9314: }
9315: fprintf(ficgp,"\n");
1.126 brouard 9316: }
9317: }
1.223 brouard 9318: }
1.187 brouard 9319: fprintf(ficgp,"##############\n#\n");
1.227 brouard 9320:
1.145 brouard 9321: /*goto avoid;*/
1.238 brouard 9322: /* 10eme Graphics of probabilities or incidences using written MLE parameters */
9323: fprintf(ficgp,"\n##############\n#10eme Graphics of probabilities or incidences\n#############\n");
1.187 brouard 9324: fprintf(ficgp,"# logi(p12/p11)=a12+b12*age+c12age*age+d12*V1+e12*V1*age\n");
9325: fprintf(ficgp,"# logi(p12/p11)=p1 +p2*age +p3*age*age+ p4*V1+ p5*V1*age\n");
9326: fprintf(ficgp,"# logi(p13/p11)=a13+b13*age+c13age*age+d13*V1+e13*V1*age\n");
9327: fprintf(ficgp,"# logi(p13/p11)=p6 +p7*age +p8*age*age+ p9*V1+ p10*V1*age\n");
9328: fprintf(ficgp,"# p12+p13+p14+p11=1=p11(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9329: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9330: fprintf(ficgp,"# p11=1/(1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9331: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age)+...)\n");
9332: fprintf(ficgp,"# p12=exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)/\n");
9333: fprintf(ficgp,"# (1+exp(a12+b12*age+c12age*age+d12*V1+e12*V1*age)\n");
9334: fprintf(ficgp,"# +exp(a13+b13*age+c13age*age+d13*V1+e13*V1*age))\n");
9335: fprintf(ficgp,"# +exp(a14+b14*age+c14age*age+d14*V1+e14*V1*age)+...)\n");
9336: fprintf(ficgp,"#\n");
1.223 brouard 9337: for(ng=1; ng<=3;ng++){ /* Number of graphics: first is logit, 2nd is probabilities, third is incidences per year*/
1.238 brouard 9338: fprintf(ficgp,"#Number of graphics: first is logit, 2nd is probabilities, third is incidences per year\n");
1.338 brouard 9339: fprintf(ficgp,"#model=1+age+%s \n",model);
1.238 brouard 9340: fprintf(ficgp,"# Type of graphic ng=%d\n",ng);
1.351 brouard 9341: /* fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcoveff,m);/\* to be checked *\/ */
9342: fprintf(ficgp,"# k1=1 to 2^%d=%d\n",cptcovs,m);/* to be checked */
1.337 brouard 9343: /* for(k1=1; k1 <=m; k1++) /\* For each combination of covariate *\/ */
1.237 brouard 9344: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 9345: /* k1=nres; */
1.338 brouard 9346: k1=TKresult[nres];
9347: if(TKresult[nres]==0) k1=1; /* To be checked for noresult */
1.337 brouard 9348: fprintf(ficgp,"\n\n# Resultline k1=%d ",k1);
1.264 brouard 9349: strcpy(gplotlabel,"(");
1.276 brouard 9350: /*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*/
1.337 brouard 9351: for (k=1; k<=cptcovs; k++){ /**< cptcovs number of SIMPLE covariates in the model V2+V1 =2 (dummy or quantit or time varying) */
9352: /* for each resultline nres, and position k, Tvresult[nres][k] gives the name of the variable and
9353: TinvDoQresult[nres][Tvresult[nres][k]] gives its value double or integer) */
9354: fprintf(ficgp," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9355: sprintf(gplotlabel+strlen(gplotlabel)," V%d=%lg ",Tvresult[nres][k],TinvDoQresult[nres][Tvresult[nres][k]]);
9356: }
9357: /* if(m != 1 && TKresult[nres]!= k1) */
9358: /* continue; */
9359: /* fprintf(ficgp,"\n\n# Combination of dummy k1=%d which is ",k1); */
9360: /* strcpy(gplotlabel,"("); */
9361: /* /\*sprintf(gplotlabel+strlen(gplotlabel)," Dummy combination %d ",k1);*\/ */
9362: /* for (k=1; k<=cptcoveff; k++){ /\* For each correspondig covariate value *\/ */
9363: /* /\* lv= decodtabm(k1,k,cptcoveff); /\\* Should be the covariate value corresponding to k1 combination and kth covariate *\\/ *\/ */
9364: /* lv= codtabm(k1,TnsdVar[Tvaraff[k]]); /\* Should be the covariate value corresponding to combination k1 and covariate k *\/ */
9365: /* /\* decodtabm(1,1,4) = 1 because h=1 k= (1) 1 1 1 *\/ */
9366: /* /\* decodtabm(1,2,4) = 1 because h=1 k= 1 (1) 1 1 *\/ */
9367: /* /\* decodtabm(13,3,4)= 2 because h=13 k= 1 1 (2) 2 *\/ */
9368: /* /\* vlv= nbcode[Tvaraff[k]][lv]; *\/ */
9369: /* vlv= nbcode[Tvaraff[k]][codtabm(k1,TnsdVar[Tvaraff[k]])]; */
9370: /* fprintf(ficgp," V%d=%d ",Tvaraff[k],vlv); */
9371: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%d ",Tvaraff[k],vlv); */
9372: /* } */
9373: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9374: /* fprintf(ficgp," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9375: /* sprintf(gplotlabel+strlen(gplotlabel)," V%d=%f ",Tvqresult[nres][resultmodel[nres][k4]],Tqresult[nres][resultmodel[nres][k4]]); */
9376: /* } */
1.264 brouard 9377: strcpy(gplotlabel+strlen(gplotlabel),")");
1.237 brouard 9378: fprintf(ficgp,"\n#\n");
1.264 brouard 9379: fprintf(ficgp,"\nset out \"%s_%d-%d-%d.svg\" ",subdirf2(optionfilefiname,"PE_"),k1,ng,nres);
1.276 brouard 9380: fprintf(ficgp,"\nset key outside ");
9381: /* fprintf(ficgp,"\nset label \"%s\" at graph 1.2,0.5 center rotate font \"Helvetica,12\"\n",gplotlabel); */
9382: fprintf(ficgp,"\nset title \"%s\" font \"Helvetica,12\"\n",gplotlabel);
1.223 brouard 9383: fprintf(ficgp,"\nset ter svg size 640, 480 ");
9384: if (ng==1){
9385: fprintf(ficgp,"\nset ylabel \"Value of the logit of the model\"\n"); /* exp(a12+b12*x) could be nice */
9386: fprintf(ficgp,"\nunset log y");
9387: }else if (ng==2){
9388: fprintf(ficgp,"\nset ylabel \"Probability\"\n");
9389: fprintf(ficgp,"\nset log y");
9390: }else if (ng==3){
9391: fprintf(ficgp,"\nset ylabel \"Quasi-incidence per year\"\n");
9392: fprintf(ficgp,"\nset log y");
9393: }else
9394: fprintf(ficgp,"\nunset title ");
9395: fprintf(ficgp,"\nplot [%.f:%.f] ",ageminpar,agemaxpar);
9396: i=1;
9397: for(k2=1; k2<=nlstate; k2++) {
9398: k3=i;
9399: for(k=1; k<=(nlstate+ndeath); k++) {
9400: if (k != k2){
9401: switch( ng) {
9402: case 1:
9403: if(nagesqr==0)
9404: fprintf(ficgp," p%d+p%d*x",i,i+1);
9405: else /* nagesqr =1 */
9406: fprintf(ficgp," p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9407: break;
9408: case 2: /* ng=2 */
9409: if(nagesqr==0)
9410: fprintf(ficgp," exp(p%d+p%d*x",i,i+1);
9411: else /* nagesqr =1 */
9412: fprintf(ficgp," exp(p%d+p%d*x+p%d*x*x",i,i+1,i+1+nagesqr);
9413: break;
9414: case 3:
9415: if(nagesqr==0)
9416: fprintf(ficgp," %f*exp(p%d+p%d*x",YEARM/stepm,i,i+1);
9417: else /* nagesqr =1 */
9418: fprintf(ficgp," %f*exp(p%d+p%d*x+p%d*x*x",YEARM/stepm,i,i+1,i+1+nagesqr);
9419: break;
9420: }
9421: ij=1;/* To be checked else nbcode[0][0] wrong */
1.237 brouard 9422: ijp=1; /* product no age */
9423: /* for(j=3; j <=ncovmodel-nagesqr; j++) { */
9424: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
1.223 brouard 9425: /* printf("Tage[%d]=%d, j=%d\n", ij, Tage[ij], j); */
1.329 brouard 9426: switch(Typevar[j]){
9427: case 1:
9428: if(cptcovage >0){ /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9429: if(j==Tage[ij]) { /* Product by age To be looked at!!*//* Bug valgrind */
9430: if(ij <=cptcovage) { /* V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1, 2 V5 and V1 */
9431: if(DummyV[j]==0){/* Bug valgrind */
9432: fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);;
9433: }else{ /* quantitative */
9434: fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9435: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9436: }
9437: ij++;
1.268 brouard 9438: }
1.237 brouard 9439: }
1.329 brouard 9440: }
9441: break;
9442: case 2:
9443: if(cptcovprod >0){
9444: if(j==Tprod[ijp]) { /* */
9445: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9446: if(ijp <=cptcovprod) { /* Product */
9447: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9448: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9449: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */
9450: fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9451: }else{ /* Vn is dummy and Vm is quanti */
9452: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9453: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9454: }
9455: }else{ /* Vn*Vm Vn is quanti */
9456: if(DummyV[Tvard[ijp][2]]==0){
9457: fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9458: }else{ /* Both quanti */
9459: fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9460: }
1.268 brouard 9461: }
1.329 brouard 9462: ijp++;
1.237 brouard 9463: }
1.329 brouard 9464: } /* end Tprod */
9465: }
9466: break;
1.349 brouard 9467: case 3:
9468: if(cptcovdageprod >0){
9469: /* if(j==Tprod[ijp]) { */ /* not necessary */
9470: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
1.350 brouard 9471: if(ijp <=cptcovprod) { /* Product Vn*Vm and age*VN*Vm*/
9472: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
9473: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9474: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */
9475: fprintf(ficgp,"+p%d*%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9476: }else{ /* Vn is dummy and Vm is quanti */
9477: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
1.350 brouard 9478: fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 9479: }
1.350 brouard 9480: }else{ /* age* Vn*Vm Vn is quanti HERE */
1.349 brouard 9481: if(DummyV[Tvard[ijp][2]]==0){
1.350 brouard 9482: fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvardk[ijp][2]],Tqinvresult[nres][Tvardk[ijp][1]]);
1.349 brouard 9483: }else{ /* Both quanti */
1.350 brouard 9484: fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 9485: }
9486: }
9487: ijp++;
9488: }
9489: /* } */ /* end Tprod */
9490: }
9491: break;
1.329 brouard 9492: case 0:
9493: /* simple covariate */
1.264 brouard 9494: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
1.237 brouard 9495: if(Dummy[j]==0){
9496: fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /* */
9497: }else{ /* quantitative */
9498: fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /* */
1.264 brouard 9499: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
1.223 brouard 9500: }
1.329 brouard 9501: /* end simple */
9502: break;
9503: default:
9504: break;
9505: } /* end switch */
1.237 brouard 9506: } /* end j */
1.329 brouard 9507: }else{ /* k=k2 */
9508: if(ng !=1 ){ /* For logit formula of log p11 is more difficult to get */
9509: fprintf(ficgp," (1.");i=i-ncovmodel;
9510: }else
9511: i=i-ncovmodel;
1.223 brouard 9512: }
1.227 brouard 9513:
1.223 brouard 9514: if(ng != 1){
9515: fprintf(ficgp,")/(1");
1.227 brouard 9516:
1.264 brouard 9517: for(cpt=1; cpt <=nlstate; cpt++){
1.223 brouard 9518: if(nagesqr==0)
1.264 brouard 9519: fprintf(ficgp,"+exp(p%d+p%d*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1);
1.223 brouard 9520: else /* nagesqr =1 */
1.264 brouard 9521: fprintf(ficgp,"+exp(p%d+p%d*x+p%d*x*x",k3+(cpt-1)*ncovmodel,k3+(cpt-1)*ncovmodel+1,k3+(cpt-1)*ncovmodel+1+nagesqr);
1.217 brouard 9522:
1.223 brouard 9523: ij=1;
1.329 brouard 9524: ijp=1;
9525: /* for(j=3; j <=ncovmodel-nagesqr; j++){ */
9526: for(j=1; j <=cptcovt; j++) { /* For each covariate of the simplified model */
9527: switch(Typevar[j]){
9528: case 1:
9529: if(cptcovage >0){
9530: if(j==Tage[ij]) { /* Bug valgrind */
9531: if(ij <=cptcovage) { /* Bug valgrind */
9532: if(DummyV[j]==0){/* Bug valgrind */
9533: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]); */
9534: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,nbcode[Tvar[j]][codtabm(k1,j)]); */
9535: fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]);
9536: /* fprintf(ficgp,"+p%d*%d*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]);; */
9537: /* fprintf(ficgp,"+p%d*%d*x",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9538: }else{ /* quantitative */
9539: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9540: fprintf(ficgp,"+p%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* Tqinvresult in decoderesult */
9541: /* fprintf(ficgp,"+p%d*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* Tqinvresult in decoderesult *\/ */
9542: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9543: }
9544: ij++;
9545: }
9546: }
9547: }
9548: break;
9549: case 2:
9550: if(cptcovprod >0){
9551: if(j==Tprod[ijp]) { /* */
9552: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9553: if(ijp <=cptcovprod) { /* Product */
9554: if(DummyV[Tvard[ijp][1]]==0){/* Vn is dummy */
9555: if(DummyV[Tvard[ijp][2]]==0){/* Vn and Vm are dummy */
9556: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */
9557: fprintf(ficgp,"+p%d*%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]);
9558: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9559: }else{ /* Vn is dummy and Vm is quanti */
9560: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
9561: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9562: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9563: }
9564: }else{ /* Vn*Vm Vn is quanti */
9565: if(DummyV[Tvard[ijp][2]]==0){
9566: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]);
9567: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9568: }else{ /* Both quanti */
9569: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]);
9570: /* fprintf(ficgp,"+p%d*%f*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9571: }
9572: }
9573: ijp++;
9574: }
9575: } /* end Tprod */
9576: } /* end if */
9577: break;
1.349 brouard 9578: case 3:
9579: if(cptcovdageprod >0){
9580: /* if(j==Tprod[ijp]) { /\* *\/ */
9581: /* printf("Tprod[%d]=%d, j=%d\n", ij, Tprod[ijp], j); */
9582: if(ijp <=cptcovprod) { /* Product */
1.350 brouard 9583: if(DummyV[Tvardk[ijp][1]]==0){/* Vn is dummy */
9584: if(DummyV[Tvardk[ijp][2]]==0){/* Vn and Vm are dummy */
1.349 brouard 9585: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],nbcode[Tvard[ijp][2]][codtabm(k1,j)]); */
1.350 brouard 9586: fprintf(ficgp,"+p%d*%d*%d*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][1]],Tinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 9587: /* fprintf(ficgp,"+p%d*%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tinvresult[nres][Tvard[ijp][2]]); */
9588: }else{ /* Vn is dummy and Vm is quanti */
9589: /* fprintf(ficgp,"+p%d*%d*%f",i+j+2+nagesqr-1,nbcode[Tvard[ijp][1]][codtabm(k1,j)],Tqinvresult[nres][Tvard[ijp][2]]); */
1.350 brouard 9590: fprintf(ficgp,"+p%d*%d*%f*x",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 9591: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9592: }
9593: }else{ /* Vn*Vm Vn is quanti */
1.350 brouard 9594: if(DummyV[Tvardk[ijp][2]]==0){
9595: fprintf(ficgp,"+p%d*%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvardk[ijp][2]],Tqinvresult[nres][Tvardk[ijp][1]]);
1.349 brouard 9596: /* fprintf(ficgp,"+p%d*%d*%f*x",i+j+2+nagesqr-1,Tinvresult[nres][Tvard[ijp][2]],Tqinvresult[nres][Tvard[ijp][1]]); */
9597: }else{ /* Both quanti */
1.350 brouard 9598: fprintf(ficgp,"+p%d*%f*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvardk[ijp][1]],Tqinvresult[nres][Tvardk[ijp][2]]);
1.349 brouard 9599: /* fprintf(ficgp,"+p%d*%f*%f*x",i+j+2+nagesqr-1,Tqinvresult[nres][Tvard[ijp][1]],Tqinvresult[nres][Tvard[ijp][2]]); */
9600: }
9601: }
9602: ijp++;
9603: }
9604: /* } /\* end Tprod *\/ */
9605: } /* end if */
9606: break;
1.329 brouard 9607: case 0:
9608: /* simple covariate */
9609: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,nbcode[Tvar[j]][codtabm(k1,j)]); /\* Valgrind bug nbcode *\/ */
9610: if(Dummy[j]==0){
9611: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9612: fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tinvresult[nres][Tvar[j]]); /* */
9613: /* fprintf(ficgp,"+p%d*%d",i+j+2+nagesqr-1,Tinvresult[nres][Tvar[j]]); /\* *\/ */
9614: }else{ /* quantitative */
9615: fprintf(ficgp,"+p%d*%f",k3+(cpt-1)*ncovmodel+1+j+nagesqr,Tqinvresult[nres][Tvar[j]]); /* */
9616: /* fprintf(ficgp,"+p%d*%f",i+j+2+nagesqr-1,Tqinvresult[nres][Tvar[j]]); /\* *\/ */
9617: /* fprintf(ficgp,"+p%d*%d*x",i+j+nagesqr-1,nbcode[Tvar[j-2]][codtabm(k1,Tvar[j-2])]); */
9618: }
9619: /* end simple */
9620: /* fprintf(ficgp,"+p%d*%d",k3+(cpt-1)*ncovmodel+1+j-2+nagesqr,nbcode[Tvar[j-2]][codtabm(k1,j-2)]);/\* Valgrind bug nbcode *\/ */
9621: break;
9622: default:
9623: break;
9624: } /* end switch */
1.223 brouard 9625: }
9626: fprintf(ficgp,")");
9627: }
9628: fprintf(ficgp,")");
9629: if(ng ==2)
1.276 brouard 9630: fprintf(ficgp," w l lw 2 lt (%d*%d+%d)%%%d+1 dt %d t \"p%d%d\" ", nlstate+ndeath, k2, k, nlstate+ndeath, k2, k2,k);
1.223 brouard 9631: else /* ng= 3 */
1.276 brouard 9632: fprintf(ficgp," w l lw 2 lt (%d*%d+%d)%%%d+1 dt %d t \"i%d%d\" ", nlstate+ndeath, k2, k, nlstate+ndeath, k2, k2,k);
1.329 brouard 9633: }else{ /* end ng <> 1 */
1.223 brouard 9634: if( k !=k2) /* logit p11 is hard to draw */
1.276 brouard 9635: fprintf(ficgp," w l lw 2 lt (%d*%d+%d)%%%d+1 dt %d t \"logit(p%d%d)\" ", nlstate+ndeath, k2, k, nlstate+ndeath, k2, k2,k);
1.223 brouard 9636: }
9637: if ((k+k2)!= (nlstate*2+ndeath) && ng != 1)
9638: fprintf(ficgp,",");
9639: if (ng == 1 && k!=k2 && (k+k2)!= (nlstate*2+ndeath))
9640: fprintf(ficgp,",");
9641: i=i+ncovmodel;
9642: } /* end k */
9643: } /* end k2 */
1.276 brouard 9644: /* fprintf(ficgp,"\n set out; unset label;set key default;\n"); */
9645: fprintf(ficgp,"\n set out; unset title;set key default;\n");
1.337 brouard 9646: } /* end resultline */
1.223 brouard 9647: } /* end ng */
9648: /* avoid: */
9649: fflush(ficgp);
1.126 brouard 9650: } /* end gnuplot */
9651:
9652:
9653: /*************** Moving average **************/
1.219 brouard 9654: /* int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav, double bageout, double fageout){ */
1.222 brouard 9655: int movingaverage(double ***probs, double bage, double fage, double ***mobaverage, int mobilav){
1.218 brouard 9656:
1.222 brouard 9657: int i, cpt, cptcod;
9658: int modcovmax =1;
9659: int mobilavrange, mob;
9660: int iage=0;
1.288 brouard 9661: int firstA1=0, firstA2=0;
1.222 brouard 9662:
1.266 brouard 9663: double sum=0., sumr=0.;
1.222 brouard 9664: double age;
1.266 brouard 9665: double *sumnewp, *sumnewm, *sumnewmr;
9666: double *agemingood, *agemaxgood;
9667: double *agemingoodr, *agemaxgoodr;
1.222 brouard 9668:
9669:
1.278 brouard 9670: /* modcovmax=2*cptcoveff; Max number of modalities. We suppose */
9671: /* a covariate has 2 modalities, should be equal to ncovcombmax */
1.222 brouard 9672:
9673: sumnewp = vector(1,ncovcombmax);
9674: sumnewm = vector(1,ncovcombmax);
1.266 brouard 9675: sumnewmr = vector(1,ncovcombmax);
1.222 brouard 9676: agemingood = vector(1,ncovcombmax);
1.266 brouard 9677: agemingoodr = vector(1,ncovcombmax);
1.222 brouard 9678: agemaxgood = vector(1,ncovcombmax);
1.266 brouard 9679: agemaxgoodr = vector(1,ncovcombmax);
1.222 brouard 9680:
9681: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
1.266 brouard 9682: sumnewm[cptcod]=0.; sumnewmr[cptcod]=0.;
1.222 brouard 9683: sumnewp[cptcod]=0.;
1.266 brouard 9684: agemingood[cptcod]=0, agemingoodr[cptcod]=0;
9685: agemaxgood[cptcod]=0, agemaxgoodr[cptcod]=0;
1.222 brouard 9686: }
9687: if (cptcovn<1) ncovcombmax=1; /* At least 1 pass */
9688:
1.266 brouard 9689: if(mobilav==-1 || mobilav==1||mobilav ==3 ||mobilav==5 ||mobilav== 7){
9690: if(mobilav==1 || mobilav==-1) mobilavrange=5; /* default */
1.222 brouard 9691: else mobilavrange=mobilav;
9692: for (age=bage; age<=fage; age++)
9693: for (i=1; i<=nlstate;i++)
9694: for (cptcod=1;cptcod<=ncovcombmax;cptcod++)
9695: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9696: /* We keep the original values on the extreme ages bage, fage and for
9697: fage+1 and bage-1 we use a 3 terms moving average; for fage+2 bage+2
9698: we use a 5 terms etc. until the borders are no more concerned.
9699: */
9700: for (mob=3;mob <=mobilavrange;mob=mob+2){
9701: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){
1.266 brouard 9702: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){
9703: sumnewm[cptcod]=0.;
9704: for (i=1; i<=nlstate;i++){
1.222 brouard 9705: mobaverage[(int)age][i][cptcod] =probs[(int)age][i][cptcod];
9706: for (cpt=1;cpt<=(mob-1)/2;cpt++){
9707: mobaverage[(int)age][i][cptcod] +=probs[(int)age-cpt][i][cptcod];
9708: mobaverage[(int)age][i][cptcod] +=probs[(int)age+cpt][i][cptcod];
9709: }
9710: mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/mob;
1.266 brouard 9711: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9712: } /* end i */
9713: if(sumnewm[cptcod] >1.e-3) mobaverage[(int)age][i][cptcod]=mobaverage[(int)age][i][cptcod]/sumnewm[cptcod]; /* Rescaling to sum one */
9714: } /* end cptcod */
1.222 brouard 9715: }/* end age */
9716: }/* end mob */
1.266 brouard 9717: }else{
9718: printf("Error internal in movingaverage, mobilav=%d.\n",mobilav);
1.222 brouard 9719: return -1;
1.266 brouard 9720: }
9721:
9722: for (cptcod=1;cptcod<=ncovcombmax;cptcod++){ /* for each combination */
1.222 brouard 9723: /* for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ */
9724: if(invalidvarcomb[cptcod]){
9725: printf("\nCombination (%d) ignored because no cases \n",cptcod);
9726: continue;
9727: }
1.219 brouard 9728:
1.266 brouard 9729: for (age=fage-(mob-1)/2; age>=bage+(mob-1)/2; age--){ /*looking for the youngest and oldest good age */
9730: sumnewm[cptcod]=0.;
9731: sumnewmr[cptcod]=0.;
9732: for (i=1; i<=nlstate;i++){
9733: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9734: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9735: }
9736: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9737: agemingoodr[cptcod]=age;
9738: }
9739: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9740: agemingood[cptcod]=age;
9741: }
9742: } /* age */
9743: for (age=bage+(mob-1)/2; age<=fage-(mob-1)/2; age++){ /*looking for the youngest and oldest good age */
1.222 brouard 9744: sumnewm[cptcod]=0.;
1.266 brouard 9745: sumnewmr[cptcod]=0.;
1.222 brouard 9746: for (i=1; i<=nlstate;i++){
9747: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9748: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9749: }
9750: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9751: agemaxgoodr[cptcod]=age;
1.222 brouard 9752: }
9753: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
1.266 brouard 9754: agemaxgood[cptcod]=age;
9755: }
9756: } /* age */
9757: /* Thus we have agemingood and agemaxgood as well as goodr for raw (preobs) */
9758: /* but they will change */
1.288 brouard 9759: firstA1=0;firstA2=0;
1.266 brouard 9760: for (age=fage-(mob-1)/2; age>=bage; age--){/* From oldest to youngest, filling up to the youngest */
9761: sumnewm[cptcod]=0.;
9762: sumnewmr[cptcod]=0.;
9763: for (i=1; i<=nlstate;i++){
9764: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9765: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9766: }
9767: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9768: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good without smoothing */
9769: agemaxgoodr[cptcod]=age; /* age min */
9770: for (i=1; i<=nlstate;i++)
9771: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9772: }else{ /* bad we change the value with the values of good ages */
9773: for (i=1; i<=nlstate;i++){
9774: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgoodr[cptcod]][i][cptcod];
9775: } /* i */
9776: } /* end bad */
9777: }else{
9778: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9779: agemaxgood[cptcod]=age;
9780: }else{ /* bad we change the value with the values of good ages */
9781: for (i=1; i<=nlstate;i++){
9782: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod];
9783: } /* i */
9784: } /* end bad */
9785: }/* end else */
9786: sum=0.;sumr=0.;
9787: for (i=1; i<=nlstate;i++){
9788: sum+=mobaverage[(int)age][i][cptcod];
9789: sumr+=probs[(int)age][i][cptcod];
9790: }
9791: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.288 brouard 9792: if(!firstA1){
9793: firstA1=1;
9794: printf("Moving average A1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you increase bage=%d. Others in log file...\n",cptcod,sumr, (int)age, (int)bage);
9795: }
9796: fprintf(ficlog,"Moving average A1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you increase bage=%d\n",cptcod,sumr, (int)age, (int)bage);
1.266 brouard 9797: } /* end bad */
9798: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9799: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.288 brouard 9800: if(!firstA2){
9801: firstA2=1;
9802: printf("Moving average A2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase bage=%d. Others in log file...\n",cptcod,sumr, (int)age, (int)bage);
9803: }
9804: fprintf(ficlog,"Moving average A2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase bage=%d\n",cptcod,sumr, (int)age, (int)bage);
1.222 brouard 9805: } /* end bad */
9806: }/* age */
1.266 brouard 9807:
9808: for (age=bage+(mob-1)/2; age<=fage; age++){/* From youngest, finding the oldest wrong */
1.222 brouard 9809: sumnewm[cptcod]=0.;
1.266 brouard 9810: sumnewmr[cptcod]=0.;
1.222 brouard 9811: for (i=1; i<=nlstate;i++){
9812: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
1.266 brouard 9813: sumnewmr[cptcod]+=probs[(int)age][i][cptcod];
9814: }
9815: if(mobilav==-1){ /* Forcing raw ages if good else agemingood */
9816: if(fabs(sumnewmr[cptcod] - 1.) <= 1.e-3) { /* good */
9817: agemingoodr[cptcod]=age;
9818: for (i=1; i<=nlstate;i++)
9819: mobaverage[(int)age][i][cptcod]=probs[(int)age][i][cptcod];
9820: }else{ /* bad we change the value with the values of good ages */
9821: for (i=1; i<=nlstate;i++){
9822: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingoodr[cptcod]][i][cptcod];
9823: } /* i */
9824: } /* end bad */
9825: }else{
9826: if(fabs(sumnewm[cptcod] - 1.) <= 1.e-3) { /* good */
9827: agemingood[cptcod]=age;
9828: }else{ /* bad */
9829: for (i=1; i<=nlstate;i++){
9830: mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod];
9831: } /* i */
9832: } /* end bad */
9833: }/* end else */
9834: sum=0.;sumr=0.;
9835: for (i=1; i<=nlstate;i++){
9836: sum+=mobaverage[(int)age][i][cptcod];
9837: sumr+=mobaverage[(int)age][i][cptcod];
1.222 brouard 9838: }
1.266 brouard 9839: if(fabs(sum - 1.) > 1.e-3) { /* bad */
1.268 brouard 9840: printf("Moving average B1: For this combination of covariate cptcod=%d, we can't get a smoothed prevalence which sums to one (%f) at any descending age! age=%d, could you decrease fage=%d?\n",cptcod, sum, (int) age, (int)fage);
1.266 brouard 9841: } /* end bad */
9842: /* else{ /\* We found some ages summing to one, we will smooth the oldest *\/ */
9843: if(fabs(sumr - 1.) > 1.e-3) { /* bad */
1.268 brouard 9844: printf("Moving average B2: For this combination of covariate cptcod=%d, the raw prevalence doesn't sums to one (%f) even with smoothed values at young ages! age=%d, could you increase fage=%d\n",cptcod,sumr, (int)age, (int)fage);
1.222 brouard 9845: } /* end bad */
9846: }/* age */
1.266 brouard 9847:
1.222 brouard 9848:
9849: for (age=bage; age<=fage; age++){
1.235 brouard 9850: /* printf("%d %d ", cptcod, (int)age); */
1.222 brouard 9851: sumnewp[cptcod]=0.;
9852: sumnewm[cptcod]=0.;
9853: for (i=1; i<=nlstate;i++){
9854: sumnewp[cptcod]+=probs[(int)age][i][cptcod];
9855: sumnewm[cptcod]+=mobaverage[(int)age][i][cptcod];
9856: /* printf("%.4f %.4f ",probs[(int)age][i][cptcod], mobaverage[(int)age][i][cptcod]); */
9857: }
9858: /* printf("%.4f %.4f \n",sumnewp[cptcod], sumnewm[cptcod]); */
9859: }
9860: /* printf("\n"); */
9861: /* } */
1.266 brouard 9862:
1.222 brouard 9863: /* brutal averaging */
1.266 brouard 9864: /* for (i=1; i<=nlstate;i++){ */
9865: /* for (age=1; age<=bage; age++){ */
9866: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemingood[cptcod]][i][cptcod]; */
9867: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9868: /* } */
9869: /* for (age=fage; age<=AGESUP; age++){ */
9870: /* mobaverage[(int)age][i][cptcod]=mobaverage[(int)agemaxgood[cptcod]][i][cptcod]; */
9871: /* /\* printf("age=%d i=%d cptcod=%d mobaverage=%.4f \n",(int)age,i, cptcod, mobaverage[(int)age][i][cptcod]); *\/ */
9872: /* } */
9873: /* } /\* end i status *\/ */
9874: /* for (i=nlstate+1; i<=nlstate+ndeath;i++){ */
9875: /* for (age=1; age<=AGESUP; age++){ */
9876: /* /\*printf("i=%d, age=%d, cptcod=%d\n",i, (int)age, cptcod);*\/ */
9877: /* mobaverage[(int)age][i][cptcod]=0.; */
9878: /* } */
9879: /* } */
1.222 brouard 9880: }/* end cptcod */
1.266 brouard 9881: free_vector(agemaxgoodr,1, ncovcombmax);
9882: free_vector(agemaxgood,1, ncovcombmax);
9883: free_vector(agemingood,1, ncovcombmax);
9884: free_vector(agemingoodr,1, ncovcombmax);
9885: free_vector(sumnewmr,1, ncovcombmax);
1.222 brouard 9886: free_vector(sumnewm,1, ncovcombmax);
9887: free_vector(sumnewp,1, ncovcombmax);
9888: return 0;
9889: }/* End movingaverage */
1.218 brouard 9890:
1.126 brouard 9891:
1.296 brouard 9892:
1.126 brouard 9893: /************** Forecasting ******************/
1.296 brouard 9894: /* void prevforecast(char fileres[], double dateintmean, double anprojd, double mprojd, double jprojd, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double ***prev, double bage, double fage, int firstpass, int lastpass, double anprojf, double p[], int cptcoveff)*/
9895: void prevforecast(char fileres[], double dateintmean, double dateprojd, double dateprojf, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double ***prev, double bage, double fage, int firstpass, int lastpass, double p[], int cptcoveff){
9896: /* dateintemean, mean date of interviews
9897: dateprojd, year, month, day of starting projection
9898: dateprojf date of end of projection;year of end of projection (same day and month as proj1).
1.126 brouard 9899: agemin, agemax range of age
9900: dateprev1 dateprev2 range of dates during which prevalence is computed
9901: */
1.296 brouard 9902: /* double anprojd, mprojd, jprojd; */
9903: /* double anprojf, mprojf, jprojf; */
1.267 brouard 9904: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
1.126 brouard 9905: double agec; /* generic age */
1.296 brouard 9906: double agelim, ppij, yp,yp1,yp2;
1.126 brouard 9907: double *popeffectif,*popcount;
9908: double ***p3mat;
1.218 brouard 9909: /* double ***mobaverage; */
1.126 brouard 9910: char fileresf[FILENAMELENGTH];
9911:
9912: agelim=AGESUP;
1.211 brouard 9913: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
9914: in each health status at the date of interview (if between dateprev1 and dateprev2).
9915: We still use firstpass and lastpass as another selection.
9916: */
1.214 brouard 9917: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
9918: /* firstpass, lastpass, stepm, weightopt, model); */
1.126 brouard 9919:
1.201 brouard 9920: strcpy(fileresf,"F_");
9921: strcat(fileresf,fileresu);
1.126 brouard 9922: if((ficresf=fopen(fileresf,"w"))==NULL) {
9923: printf("Problem with forecast resultfile: %s\n", fileresf);
9924: fprintf(ficlog,"Problem with forecast resultfile: %s\n", fileresf);
9925: }
1.235 brouard 9926: printf("\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
9927: fprintf(ficlog,"\nComputing forecasting: result on file '%s', please wait... \n", fileresf);
1.126 brouard 9928:
1.225 brouard 9929: if (cptcoveff==0) ncodemax[cptcoveff]=1;
1.126 brouard 9930:
9931:
9932: stepsize=(int) (stepm+YEARM-1)/YEARM;
9933: if (stepm<=12) stepsize=1;
9934: if(estepm < stepm){
9935: printf ("Problem %d lower than %d\n",estepm, stepm);
9936: }
1.270 brouard 9937: else{
9938: hstepm=estepm;
9939: }
9940: if(estepm > stepm){ /* Yes every two year */
9941: stepsize=2;
9942: }
1.296 brouard 9943: hstepm=hstepm/stepm;
1.126 brouard 9944:
1.296 brouard 9945:
9946: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
9947: /* fractional in yp1 *\/ */
9948: /* aintmean=yp; */
9949: /* yp2=modf((yp1*12),&yp); */
9950: /* mintmean=yp; */
9951: /* yp1=modf((yp2*30.5),&yp); */
9952: /* jintmean=yp; */
9953: /* if(jintmean==0) jintmean=1; */
9954: /* if(mintmean==0) mintmean=1; */
1.126 brouard 9955:
1.296 brouard 9956:
9957: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */
9958: /* date2dmy(dateprojd,&jprojd, &mprojd, &anprojd); */
9959: /* date2dmy(dateprojf,&jprojf, &mprojf, &anprojf); */
1.351 brouard 9960: /* i1=pow(2,cptcoveff); */
9961: /* if (cptcovn < 1){i1=1;} */
1.126 brouard 9962:
1.296 brouard 9963: fprintf(ficresf,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.126 brouard 9964:
9965: fprintf(ficresf,"#****** Routine prevforecast **\n");
1.227 brouard 9966:
1.126 brouard 9967: /* if (h==(int)(YEARM*yearp)){ */
1.351 brouard 9968: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
9969: k=TKresult[nres];
9970: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
9971: /* for(k=1; k<=i1;k++){ /\* We want to find the combination k corresponding to the values of the dummies given in this resut line (to be cleaned one day) *\/ */
9972: /* if(i1 != 1 && TKresult[nres]!= k) */
9973: /* continue; */
9974: /* if(invalidvarcomb[k]){ */
9975: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
9976: /* continue; */
9977: /* } */
1.227 brouard 9978: fprintf(ficresf,"\n#****** hpijx=probability over h years, hp.jx is weighted by observed prev \n#");
1.351 brouard 9979: for(j=1;j<=cptcovs;j++){
9980: /* for(j=1;j<=cptcoveff;j++) { */
9981: /* /\* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); *\/ */
9982: /* fprintf(ficresf," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
9983: /* } */
9984: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
9985: /* fprintf(ficresf," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
9986: /* } */
9987: fprintf(ficresf," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.235 brouard 9988: }
1.351 brouard 9989:
1.227 brouard 9990: fprintf(ficresf," yearproj age");
9991: for(j=1; j<=nlstate+ndeath;j++){
9992: for(i=1; i<=nlstate;i++)
9993: fprintf(ficresf," p%d%d",i,j);
9994: fprintf(ficresf," wp.%d",j);
9995: }
1.296 brouard 9996: for (yearp=0; yearp<=(anprojf-anprojd);yearp +=stepsize) {
1.227 brouard 9997: fprintf(ficresf,"\n");
1.296 brouard 9998: fprintf(ficresf,"\n# Forecasting at date %.lf/%.lf/%.lf ",jprojd,mprojd,anprojd+yearp);
1.270 brouard 9999: /* for (agec=fage; agec>=(ageminpar-1); agec--){ */
10000: for (agec=fage; agec>=(bage); agec--){
1.227 brouard 10001: nhstepm=(int) rint((agelim-agec)*YEARM/stepm);
10002: nhstepm = nhstepm/hstepm;
10003: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10004: oldm=oldms;savm=savms;
1.268 brouard 10005: /* We compute pii at age agec over nhstepm);*/
1.235 brouard 10006: hpxij(p3mat,nhstepm,agec,hstepm,p,nlstate,stepm,oldm,savm, k,nres);
1.268 brouard 10007: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
1.227 brouard 10008: for (h=0; h<=nhstepm; h++){
10009: if (h*hstepm/YEARM*stepm ==yearp) {
1.268 brouard 10010: break;
10011: }
10012: }
10013: fprintf(ficresf,"\n");
1.351 brouard 10014: /* for(j=1;j<=cptcoveff;j++) */
10015: for(j=1;j<=cptcovs;j++)
10016: fprintf(ficresf,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.332 brouard 10017: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Tvaraff not correct *\/ */
1.351 brouard 10018: /* fprintf(ficresf,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* TnsdVar[Tvaraff] correct *\/ */
1.296 brouard 10019: fprintf(ficresf,"%.f %.f ",anprojd+yearp,agec+h*hstepm/YEARM*stepm);
1.268 brouard 10020:
10021: for(j=1; j<=nlstate+ndeath;j++) {
10022: ppij=0.;
10023: for(i=1; i<=nlstate;i++) {
1.278 brouard 10024: if (mobilav>=1)
10025: ppij=ppij+p3mat[i][j][h]*prev[(int)agec][i][k];
10026: else { /* even if mobilav==-1 we use mobaverage, probs may not sums to 1 */
10027: ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k];
10028: }
1.268 brouard 10029: fprintf(ficresf," %.3f", p3mat[i][j][h]);
10030: } /* end i */
10031: fprintf(ficresf," %.3f", ppij);
10032: }/* end j */
1.227 brouard 10033: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10034: } /* end agec */
1.266 brouard 10035: /* diffyear=(int) anproj1+yearp-ageminpar-1; */
10036: /*printf("Prevforecast %d+%d-%d=diffyear=%d\n",(int) anproj1, (int)yearp,(int)ageminpar,(int) anproj1-(int)ageminpar);*/
1.227 brouard 10037: } /* end yearp */
10038: } /* end k */
1.219 brouard 10039:
1.126 brouard 10040: fclose(ficresf);
1.215 brouard 10041: printf("End of Computing forecasting \n");
10042: fprintf(ficlog,"End of Computing forecasting\n");
10043:
1.126 brouard 10044: }
10045:
1.269 brouard 10046: /************** Back Forecasting ******************/
1.296 brouard 10047: /* void prevbackforecast(char fileres[], double ***prevacurrent, double anback1, double mback1, double jback1, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double anback2, double p[], int cptcoveff){ */
10048: void prevbackforecast(char fileres[], double ***prevacurrent, double dateintmean, double dateprojd, double dateprojf, double ageminpar, double agemax, double dateprev1, double dateprev2, int mobilav, double bage, double fage, int firstpass, int lastpass, double p[], int cptcoveff){
10049: /* back1, year, month, day of starting backprojection
1.267 brouard 10050: agemin, agemax range of age
10051: dateprev1 dateprev2 range of dates during which prevalence is computed
1.269 brouard 10052: anback2 year of end of backprojection (same day and month as back1).
10053: prevacurrent and prev are prevalences.
1.267 brouard 10054: */
10055: int yearp, stepsize, hstepm, nhstepm, j, k, cptcod, i, h, i1, k4, nres=0;
10056: double agec; /* generic age */
1.302 brouard 10057: double agelim, ppij, ppi, yp,yp1,yp2; /* ,jintmean,mintmean,aintmean;*/
1.267 brouard 10058: double *popeffectif,*popcount;
10059: double ***p3mat;
10060: /* double ***mobaverage; */
10061: char fileresfb[FILENAMELENGTH];
10062:
1.268 brouard 10063: agelim=AGEINF;
1.267 brouard 10064: /* Compute observed prevalence between dateprev1 and dateprev2 by counting the number of people
10065: in each health status at the date of interview (if between dateprev1 and dateprev2).
10066: We still use firstpass and lastpass as another selection.
10067: */
10068: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint,strstart,\ */
10069: /* firstpass, lastpass, stepm, weightopt, model); */
10070:
10071: /*Do we need to compute prevalence again?*/
10072:
10073: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
10074:
10075: strcpy(fileresfb,"FB_");
10076: strcat(fileresfb,fileresu);
10077: if((ficresfb=fopen(fileresfb,"w"))==NULL) {
10078: printf("Problem with back forecast resultfile: %s\n", fileresfb);
10079: fprintf(ficlog,"Problem with back forecast resultfile: %s\n", fileresfb);
10080: }
10081: printf("\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10082: fprintf(ficlog,"\nComputing back forecasting: result on file '%s', please wait... \n", fileresfb);
10083:
10084: if (cptcoveff==0) ncodemax[cptcoveff]=1;
10085:
10086:
10087: stepsize=(int) (stepm+YEARM-1)/YEARM;
10088: if (stepm<=12) stepsize=1;
10089: if(estepm < stepm){
10090: printf ("Problem %d lower than %d\n",estepm, stepm);
10091: }
1.270 brouard 10092: else{
10093: hstepm=estepm;
10094: }
10095: if(estepm >= stepm){ /* Yes every two year */
10096: stepsize=2;
10097: }
1.267 brouard 10098:
10099: hstepm=hstepm/stepm;
1.296 brouard 10100: /* yp1=modf(dateintmean,&yp);/\* extracts integral of datemean in yp and */
10101: /* fractional in yp1 *\/ */
10102: /* aintmean=yp; */
10103: /* yp2=modf((yp1*12),&yp); */
10104: /* mintmean=yp; */
10105: /* yp1=modf((yp2*30.5),&yp); */
10106: /* jintmean=yp; */
10107: /* if(jintmean==0) jintmean=1; */
10108: /* if(mintmean==0) jintmean=1; */
1.267 brouard 10109:
1.351 brouard 10110: /* i1=pow(2,cptcoveff); */
10111: /* if (cptcovn < 1){i1=1;} */
1.267 brouard 10112:
1.296 brouard 10113: fprintf(ficresfb,"# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
10114: printf("# Mean day of interviews %.lf/%.lf/%.lf (%.2f) between %.2f and %.2f \n",jintmean,mintmean,aintmean,dateintmean,dateprev1,dateprev2);
1.267 brouard 10115:
10116: fprintf(ficresfb,"#****** Routine prevbackforecast **\n");
10117:
1.351 brouard 10118: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10119: k=TKresult[nres];
10120: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
10121: /* for(k=1; k<=i1;k++){ */
10122: /* if(i1 != 1 && TKresult[nres]!= k) */
10123: /* continue; */
10124: /* if(invalidvarcomb[k]){ */
10125: /* printf("\nCombination (%d) projection ignored because no cases \n",k); */
10126: /* continue; */
10127: /* } */
1.268 brouard 10128: fprintf(ficresfb,"\n#****** hbijx=probability over h years, hb.jx is weighted by observed prev \n#");
1.351 brouard 10129: for(j=1;j<=cptcovs;j++){
10130: /* for(j=1;j<=cptcoveff;j++) { */
10131: /* fprintf(ficresfb," V%d (=) %d",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10132: /* } */
10133: fprintf(ficresfb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.267 brouard 10134: }
1.351 brouard 10135: /* fprintf(ficrespij,"******\n"); */
10136: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
10137: /* fprintf(ficresfb," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
10138: /* } */
1.267 brouard 10139: fprintf(ficresfb," yearbproj age");
10140: for(j=1; j<=nlstate+ndeath;j++){
10141: for(i=1; i<=nlstate;i++)
1.268 brouard 10142: fprintf(ficresfb," b%d%d",i,j);
10143: fprintf(ficresfb," b.%d",j);
1.267 brouard 10144: }
1.296 brouard 10145: for (yearp=0; yearp>=(anbackf-anbackd);yearp -=stepsize) {
1.267 brouard 10146: /* for (yearp=0; yearp<=(anproj2-anproj1);yearp +=stepsize) { */
10147: fprintf(ficresfb,"\n");
1.296 brouard 10148: fprintf(ficresfb,"\n# Back Forecasting at date %.lf/%.lf/%.lf ",jbackd,mbackd,anbackd+yearp);
1.273 brouard 10149: /* printf("\n# Back Forecasting at date %.lf/%.lf/%.lf ",jback1,mback1,anback1+yearp); */
1.270 brouard 10150: /* for (agec=bage; agec<=agemax-1; agec++){ /\* testing *\/ */
10151: for (agec=bage; agec<=fage; agec++){ /* testing */
1.268 brouard 10152: /* We compute bij at age agec over nhstepm, nhstepm decreases when agec increases because of agemax;*/
1.271 brouard 10153: nhstepm=(int) (agec-agelim) *YEARM/stepm;/* nhstepm=(int) rint((agec-agelim)*YEARM/stepm);*/
1.267 brouard 10154: nhstepm = nhstepm/hstepm;
10155: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10156: oldm=oldms;savm=savms;
1.268 brouard 10157: /* computes hbxij at age agec over 1 to nhstepm */
1.271 brouard 10158: /* printf("####prevbackforecast debug agec=%.2f nhstepm=%d\n",agec, nhstepm);fflush(stdout); */
1.267 brouard 10159: hbxij(p3mat,nhstepm,agec,hstepm,p,prevacurrent,nlstate,stepm, k, nres);
1.268 brouard 10160: /* hpxij(p3mat,nhstepm,agec,hstepm,p, nlstate,stepm,oldm,savm, k,nres); */
10161: /* Then we print p3mat for h corresponding to the right agec+h*stepms=yearp */
10162: /* printf(" agec=%.2f\n",agec);fflush(stdout); */
1.267 brouard 10163: for (h=0; h<=nhstepm; h++){
1.268 brouard 10164: if (h*hstepm/YEARM*stepm ==-yearp) {
10165: break;
10166: }
10167: }
10168: fprintf(ficresfb,"\n");
1.351 brouard 10169: /* for(j=1;j<=cptcoveff;j++) */
10170: for(j=1;j<=cptcovs;j++)
10171: fprintf(ficresfb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10172: /* fprintf(ficresfb,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.296 brouard 10173: fprintf(ficresfb,"%.f %.f ",anbackd+yearp,agec-h*hstepm/YEARM*stepm);
1.268 brouard 10174: for(i=1; i<=nlstate+ndeath;i++) {
10175: ppij=0.;ppi=0.;
10176: for(j=1; j<=nlstate;j++) {
10177: /* if (mobilav==1) */
1.269 brouard 10178: ppij=ppij+p3mat[i][j][h]*prevacurrent[(int)agec][j][k];
10179: ppi=ppi+prevacurrent[(int)agec][j][k];
10180: /* ppij=ppij+p3mat[i][j][h]*mobaverage[(int)agec][j][k]; */
10181: /* ppi=ppi+mobaverage[(int)agec][j][k]; */
1.267 brouard 10182: /* else { */
10183: /* ppij=ppij+p3mat[i][j][h]*probs[(int)(agec)][i][k]; */
10184: /* } */
1.268 brouard 10185: fprintf(ficresfb," %.3f", p3mat[i][j][h]);
10186: } /* end j */
10187: if(ppi <0.99){
10188: printf("Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10189: fprintf(ficlog,"Error in prevbackforecast, prevalence doesn't sum to 1 for state %d: %3f\n",i, ppi);
10190: }
10191: fprintf(ficresfb," %.3f", ppij);
10192: }/* end j */
1.267 brouard 10193: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
10194: } /* end agec */
10195: } /* end yearp */
10196: } /* end k */
1.217 brouard 10197:
1.267 brouard 10198: /* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
1.217 brouard 10199:
1.267 brouard 10200: fclose(ficresfb);
10201: printf("End of Computing Back forecasting \n");
10202: fprintf(ficlog,"End of Computing Back forecasting\n");
1.218 brouard 10203:
1.267 brouard 10204: }
1.217 brouard 10205:
1.269 brouard 10206: /* Variance of prevalence limit: varprlim */
10207: void varprlim(char fileresu[], int nresult, double ***prevacurrent, int mobilavproj, double bage, double fage, double **prlim, int *ncvyearp, double ftolpl, double p[], double **matcov, double *delti, int stepm, int cptcoveff){
1.288 brouard 10208: /*------- Variance of forward period (stable) prevalence------*/
1.269 brouard 10209:
10210: char fileresvpl[FILENAMELENGTH];
10211: FILE *ficresvpl;
10212: double **oldm, **savm;
10213: double **varpl; /* Variances of prevalence limits by age */
10214: int i1, k, nres, j ;
10215:
10216: strcpy(fileresvpl,"VPL_");
10217: strcat(fileresvpl,fileresu);
10218: if((ficresvpl=fopen(fileresvpl,"w"))==NULL) {
1.288 brouard 10219: printf("Problem with variance of forward period (stable) prevalence resultfile: %s\n", fileresvpl);
1.269 brouard 10220: exit(0);
10221: }
1.288 brouard 10222: printf("Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(stdout);
10223: fprintf(ficlog, "Computing Variance-covariance of forward period (stable) prevalence: file '%s' ...", fileresvpl);fflush(ficlog);
1.269 brouard 10224:
10225: /*for(cptcov=1,k=0;cptcov<=i1;cptcov++){
10226: for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*/
10227:
10228: i1=pow(2,cptcoveff);
10229: if (cptcovn < 1){i1=1;}
10230:
1.337 brouard 10231: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10232: k=TKresult[nres];
1.338 brouard 10233: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10234: /* for(k=1; k<=i1;k++){ /\* We find the combination equivalent to result line values of dummies *\/ */
1.269 brouard 10235: if(i1 != 1 && TKresult[nres]!= k)
10236: continue;
10237: fprintf(ficresvpl,"\n#****** ");
10238: printf("\n#****** ");
10239: fprintf(ficlog,"\n#****** ");
1.337 brouard 10240: for(j=1;j<=cptcovs;j++) {
10241: fprintf(ficresvpl,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10242: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10243: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
10244: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10245: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.269 brouard 10246: }
1.337 brouard 10247: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10248: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10249: /* fprintf(ficresvpl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10250: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10251: /* } */
1.269 brouard 10252: fprintf(ficresvpl,"******\n");
10253: printf("******\n");
10254: fprintf(ficlog,"******\n");
10255:
10256: varpl=matrix(1,nlstate,(int) bage, (int) fage);
10257: oldm=oldms;savm=savms;
10258: varprevlim(fileresvpl, ficresvpl, varpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, ncvyearp, k, strstart, nres);
10259: free_matrix(varpl,1,nlstate,(int) bage, (int)fage);
10260: /*}*/
10261: }
10262:
10263: fclose(ficresvpl);
1.288 brouard 10264: printf("done variance-covariance of forward period prevalence\n");fflush(stdout);
10265: fprintf(ficlog,"done variance-covariance of forward period prevalence\n");fflush(ficlog);
1.269 brouard 10266:
10267: }
10268: /* Variance of back prevalence: varbprlim */
10269: void varbprlim(char fileresu[], int nresult, double ***prevacurrent, int mobilavproj, double bage, double fage, double **bprlim, int *ncvyearp, double ftolpl, double p[], double **matcov, double *delti, int stepm, int cptcoveff){
10270: /*------- Variance of back (stable) prevalence------*/
10271:
10272: char fileresvbl[FILENAMELENGTH];
10273: FILE *ficresvbl;
10274:
10275: double **oldm, **savm;
10276: double **varbpl; /* Variances of back prevalence limits by age */
10277: int i1, k, nres, j ;
10278:
10279: strcpy(fileresvbl,"VBL_");
10280: strcat(fileresvbl,fileresu);
10281: if((ficresvbl=fopen(fileresvbl,"w"))==NULL) {
10282: printf("Problem with variance of back (stable) prevalence resultfile: %s\n", fileresvbl);
10283: exit(0);
10284: }
10285: printf("Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(stdout);
10286: fprintf(ficlog, "Computing Variance-covariance of back (stable) prevalence: file '%s' ...", fileresvbl);fflush(ficlog);
10287:
10288:
10289: i1=pow(2,cptcoveff);
10290: if (cptcovn < 1){i1=1;}
10291:
1.337 brouard 10292: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
10293: k=TKresult[nres];
1.338 brouard 10294: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 10295: /* for(k=1; k<=i1;k++){ */
10296: /* if(i1 != 1 && TKresult[nres]!= k) */
10297: /* continue; */
1.269 brouard 10298: fprintf(ficresvbl,"\n#****** ");
10299: printf("\n#****** ");
10300: fprintf(ficlog,"\n#****** ");
1.337 brouard 10301: for (j=1; j<= cptcovs; j++){ /* For each selected (single) quantitative value */
1.338 brouard 10302: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10303: fprintf(ficresvbl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
10304: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][resultmodel[nres][j]]);
1.337 brouard 10305: /* for(j=1;j<=cptcoveff;j++) { */
10306: /* fprintf(ficresvbl,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10307: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10308: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
10309: /* } */
10310: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
10311: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10312: /* fprintf(ficresvbl," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
10313: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
1.269 brouard 10314: }
10315: fprintf(ficresvbl,"******\n");
10316: printf("******\n");
10317: fprintf(ficlog,"******\n");
10318:
10319: varbpl=matrix(1,nlstate,(int) bage, (int) fage);
10320: oldm=oldms;savm=savms;
10321:
10322: varbrevlim(fileresvbl, ficresvbl, varbpl, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, bprlim, ftolpl, mobilavproj, ncvyearp, k, strstart, nres);
10323: free_matrix(varbpl,1,nlstate,(int) bage, (int)fage);
10324: /*}*/
10325: }
10326:
10327: fclose(ficresvbl);
10328: printf("done variance-covariance of back prevalence\n");fflush(stdout);
10329: fprintf(ficlog,"done variance-covariance of back prevalence\n");fflush(ficlog);
10330:
10331: } /* End of varbprlim */
10332:
1.126 brouard 10333: /************** Forecasting *****not tested NB*************/
1.227 brouard 10334: /* void populforecast(char fileres[], double anpyram,double mpyram,double jpyram,double ageminpar, double agemax,double dateprev1, double dateprev2s, int mobilav, double agedeb, double fage, int popforecast, char popfile[], double anpyram1,double p[], int i2){ */
1.126 brouard 10335:
1.227 brouard 10336: /* int cpt, stepsize, hstepm, nhstepm, j,k,c, cptcod, i,h; */
10337: /* int *popage; */
10338: /* double calagedatem, agelim, kk1, kk2; */
10339: /* double *popeffectif,*popcount; */
10340: /* double ***p3mat,***tabpop,***tabpopprev; */
10341: /* /\* double ***mobaverage; *\/ */
10342: /* char filerespop[FILENAMELENGTH]; */
1.126 brouard 10343:
1.227 brouard 10344: /* tabpop= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10345: /* tabpopprev= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10346: /* agelim=AGESUP; */
10347: /* calagedatem=(anpyram+mpyram/12.+jpyram/365.-dateintmean)*YEARM; */
1.126 brouard 10348:
1.227 brouard 10349: /* prevalence(probs, ageminpar, agemax, s, agev, nlstate, imx, Tvar, nbcode, ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass); */
1.126 brouard 10350:
10351:
1.227 brouard 10352: /* strcpy(filerespop,"POP_"); */
10353: /* strcat(filerespop,fileresu); */
10354: /* if((ficrespop=fopen(filerespop,"w"))==NULL) { */
10355: /* printf("Problem with forecast resultfile: %s\n", filerespop); */
10356: /* fprintf(ficlog,"Problem with forecast resultfile: %s\n", filerespop); */
10357: /* } */
10358: /* printf("Computing forecasting: result on file '%s' \n", filerespop); */
10359: /* fprintf(ficlog,"Computing forecasting: result on file '%s' \n", filerespop); */
1.126 brouard 10360:
1.227 brouard 10361: /* if (cptcoveff==0) ncodemax[cptcoveff]=1; */
1.126 brouard 10362:
1.227 brouard 10363: /* /\* if (mobilav!=0) { *\/ */
10364: /* /\* mobaverage= ma3x(1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
10365: /* /\* if (movingaverage(probs, ageminpar, fage, mobaverage,mobilav)!=0){ *\/ */
10366: /* /\* fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10367: /* /\* printf(" Error in movingaverage mobilav=%d\n",mobilav); *\/ */
10368: /* /\* } *\/ */
10369: /* /\* } *\/ */
1.126 brouard 10370:
1.227 brouard 10371: /* stepsize=(int) (stepm+YEARM-1)/YEARM; */
10372: /* if (stepm<=12) stepsize=1; */
1.126 brouard 10373:
1.227 brouard 10374: /* agelim=AGESUP; */
1.126 brouard 10375:
1.227 brouard 10376: /* hstepm=1; */
10377: /* hstepm=hstepm/stepm; */
1.218 brouard 10378:
1.227 brouard 10379: /* if (popforecast==1) { */
10380: /* if((ficpop=fopen(popfile,"r"))==NULL) { */
10381: /* printf("Problem with population file : %s\n",popfile);exit(0); */
10382: /* fprintf(ficlog,"Problem with population file : %s\n",popfile);exit(0); */
10383: /* } */
10384: /* popage=ivector(0,AGESUP); */
10385: /* popeffectif=vector(0,AGESUP); */
10386: /* popcount=vector(0,AGESUP); */
1.126 brouard 10387:
1.227 brouard 10388: /* i=1; */
10389: /* while ((c=fscanf(ficpop,"%d %lf\n",&popage[i],&popcount[i])) != EOF) i=i+1; */
1.218 brouard 10390:
1.227 brouard 10391: /* imx=i; */
10392: /* for (i=1; i<imx;i++) popeffectif[popage[i]]=popcount[i]; */
10393: /* } */
1.218 brouard 10394:
1.227 brouard 10395: /* for(cptcov=1,k=0;cptcov<=i2;cptcov++){ */
10396: /* for(cptcod=1;cptcod<=ncodemax[cptcoveff];cptcod++){ */
10397: /* k=k+1; */
10398: /* fprintf(ficrespop,"\n#******"); */
10399: /* for(j=1;j<=cptcoveff;j++) { */
10400: /* fprintf(ficrespop," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */
10401: /* } */
10402: /* fprintf(ficrespop,"******\n"); */
10403: /* fprintf(ficrespop,"# Age"); */
10404: /* for(j=1; j<=nlstate+ndeath;j++) fprintf(ficrespop," P.%d",j); */
10405: /* if (popforecast==1) fprintf(ficrespop," [Population]"); */
1.126 brouard 10406:
1.227 brouard 10407: /* for (cpt=0; cpt<=0;cpt++) { */
10408: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
1.126 brouard 10409:
1.227 brouard 10410: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10411: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10412: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10413:
1.227 brouard 10414: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10415: /* oldm=oldms;savm=savms; */
10416: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
1.218 brouard 10417:
1.227 brouard 10418: /* for (h=0; h<=nhstepm; h++){ */
10419: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10420: /* fprintf(ficrespop,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10421: /* } */
10422: /* for(j=1; j<=nlstate+ndeath;j++) { */
10423: /* kk1=0.;kk2=0; */
10424: /* for(i=1; i<=nlstate;i++) { */
10425: /* if (mobilav==1) */
10426: /* kk1=kk1+p3mat[i][j][h]*mobaverage[(int)agedeb+1][i][cptcod]; */
10427: /* else { */
10428: /* kk1=kk1+p3mat[i][j][h]*probs[(int)(agedeb+1)][i][cptcod]; */
10429: /* } */
10430: /* } */
10431: /* if (h==(int)(calagedatem+12*cpt)){ */
10432: /* tabpop[(int)(agedeb)][j][cptcod]=kk1; */
10433: /* /\*fprintf(ficrespop," %.3f", kk1); */
10434: /* if (popforecast==1) fprintf(ficrespop," [%.f]", kk1*popeffectif[(int)agedeb+1]);*\/ */
10435: /* } */
10436: /* } */
10437: /* for(i=1; i<=nlstate;i++){ */
10438: /* kk1=0.; */
10439: /* for(j=1; j<=nlstate;j++){ */
10440: /* kk1= kk1+tabpop[(int)(agedeb)][j][cptcod]; */
10441: /* } */
10442: /* tabpopprev[(int)(agedeb)][i][cptcod]=tabpop[(int)(agedeb)][i][cptcod]/kk1*popeffectif[(int)(agedeb+(calagedatem+12*cpt)*hstepm/YEARM*stepm-1)]; */
10443: /* } */
1.218 brouard 10444:
1.227 brouard 10445: /* if (h==(int)(calagedatem+12*cpt)) */
10446: /* for(j=1; j<=nlstate;j++) */
10447: /* fprintf(ficrespop," %15.2f",tabpopprev[(int)(agedeb+1)][j][cptcod]); */
10448: /* } */
10449: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10450: /* } */
10451: /* } */
1.218 brouard 10452:
1.227 brouard 10453: /* /\******\/ */
1.218 brouard 10454:
1.227 brouard 10455: /* for (cpt=1; cpt<=(anpyram1-anpyram);cpt++) { */
10456: /* fprintf(ficrespop,"\n\n# Forecasting at date %.lf/%.lf/%.lf ",jpyram,mpyram,anpyram+cpt); */
10457: /* for (agedeb=(fage-((int)calagedatem %12/12.)); agedeb>=(ageminpar-((int)calagedatem %12)/12.); agedeb--){ */
10458: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); */
10459: /* nhstepm = nhstepm/hstepm; */
1.126 brouard 10460:
1.227 brouard 10461: /* p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10462: /* oldm=oldms;savm=savms; */
10463: /* hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
10464: /* for (h=0; h<=nhstepm; h++){ */
10465: /* if (h==(int) (calagedatem+YEARM*cpt)) { */
10466: /* fprintf(ficresf,"\n %3.f ",agedeb+h*hstepm/YEARM*stepm); */
10467: /* } */
10468: /* for(j=1; j<=nlstate+ndeath;j++) { */
10469: /* kk1=0.;kk2=0; */
10470: /* for(i=1; i<=nlstate;i++) { */
10471: /* kk1=kk1+p3mat[i][j][h]*tabpopprev[(int)agedeb+1][i][cptcod]; */
10472: /* } */
10473: /* if (h==(int)(calagedatem+12*cpt)) fprintf(ficresf," %15.2f", kk1); */
10474: /* } */
10475: /* } */
10476: /* free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); */
10477: /* } */
10478: /* } */
10479: /* } */
10480: /* } */
1.218 brouard 10481:
1.227 brouard 10482: /* /\* if (mobilav!=0) free_ma3x(mobaverage,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); *\/ */
1.218 brouard 10483:
1.227 brouard 10484: /* if (popforecast==1) { */
10485: /* free_ivector(popage,0,AGESUP); */
10486: /* free_vector(popeffectif,0,AGESUP); */
10487: /* free_vector(popcount,0,AGESUP); */
10488: /* } */
10489: /* free_ma3x(tabpop,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10490: /* free_ma3x(tabpopprev,1, AGESUP,1,NCOVMAX, 1,NCOVMAX); */
10491: /* fclose(ficrespop); */
10492: /* } /\* End of popforecast *\/ */
1.218 brouard 10493:
1.126 brouard 10494: int fileappend(FILE *fichier, char *optionfich)
10495: {
10496: if((fichier=fopen(optionfich,"a"))==NULL) {
10497: printf("Problem with file: %s\n", optionfich);
10498: fprintf(ficlog,"Problem with file: %s\n", optionfich);
10499: return (0);
10500: }
10501: fflush(fichier);
10502: return (1);
10503: }
10504:
10505:
10506: /**************** function prwizard **********************/
10507: void prwizard(int ncovmodel, int nlstate, int ndeath, char model[], FILE *ficparo)
10508: {
10509:
10510: /* Wizard to print covariance matrix template */
10511:
1.164 brouard 10512: char ca[32], cb[32];
10513: int i,j, k, li, lj, lk, ll, jj, npar, itimes;
1.126 brouard 10514: int numlinepar;
10515:
10516: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10517: fprintf(ficparo,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
10518: for(i=1; i <=nlstate; i++){
10519: jj=0;
10520: for(j=1; j <=nlstate+ndeath; j++){
10521: if(j==i) continue;
10522: jj++;
10523: /*ca[0]= k+'a'-1;ca[1]='\0';*/
10524: printf("%1d%1d",i,j);
10525: fprintf(ficparo,"%1d%1d",i,j);
10526: for(k=1; k<=ncovmodel;k++){
10527: /* printf(" %lf",param[i][j][k]); */
10528: /* fprintf(ficparo," %lf",param[i][j][k]); */
10529: printf(" 0.");
10530: fprintf(ficparo," 0.");
10531: }
10532: printf("\n");
10533: fprintf(ficparo,"\n");
10534: }
10535: }
10536: printf("# Scales (for hessian or gradient estimation)\n");
10537: fprintf(ficparo,"# Scales (for hessian or gradient estimation)\n");
10538: npar= (nlstate+ndeath-1)*nlstate*ncovmodel; /* Number of parameters*/
10539: for(i=1; i <=nlstate; i++){
10540: jj=0;
10541: for(j=1; j <=nlstate+ndeath; j++){
10542: if(j==i) continue;
10543: jj++;
10544: fprintf(ficparo,"%1d%1d",i,j);
10545: printf("%1d%1d",i,j);
10546: fflush(stdout);
10547: for(k=1; k<=ncovmodel;k++){
10548: /* printf(" %le",delti3[i][j][k]); */
10549: /* fprintf(ficparo," %le",delti3[i][j][k]); */
10550: printf(" 0.");
10551: fprintf(ficparo," 0.");
10552: }
10553: numlinepar++;
10554: printf("\n");
10555: fprintf(ficparo,"\n");
10556: }
10557: }
10558: printf("# Covariance matrix\n");
10559: /* # 121 Var(a12)\n\ */
10560: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10561: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
10562: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
10563: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
10564: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
10565: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
10566: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10567: fflush(stdout);
10568: fprintf(ficparo,"# Covariance matrix\n");
10569: /* # 121 Var(a12)\n\ */
10570: /* # 122 Cov(b12,a12) Var(b12)\n\ */
10571: /* # ...\n\ */
10572: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
10573:
10574: for(itimes=1;itimes<=2;itimes++){
10575: jj=0;
10576: for(i=1; i <=nlstate; i++){
10577: for(j=1; j <=nlstate+ndeath; j++){
10578: if(j==i) continue;
10579: for(k=1; k<=ncovmodel;k++){
10580: jj++;
10581: ca[0]= k+'a'-1;ca[1]='\0';
10582: if(itimes==1){
10583: printf("#%1d%1d%d",i,j,k);
10584: fprintf(ficparo,"#%1d%1d%d",i,j,k);
10585: }else{
10586: printf("%1d%1d%d",i,j,k);
10587: fprintf(ficparo,"%1d%1d%d",i,j,k);
10588: /* printf(" %.5le",matcov[i][j]); */
10589: }
10590: ll=0;
10591: for(li=1;li <=nlstate; li++){
10592: for(lj=1;lj <=nlstate+ndeath; lj++){
10593: if(lj==li) continue;
10594: for(lk=1;lk<=ncovmodel;lk++){
10595: ll++;
10596: if(ll<=jj){
10597: cb[0]= lk +'a'-1;cb[1]='\0';
10598: if(ll<jj){
10599: if(itimes==1){
10600: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10601: fprintf(ficparo," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
10602: }else{
10603: printf(" 0.");
10604: fprintf(ficparo," 0.");
10605: }
10606: }else{
10607: if(itimes==1){
10608: printf(" Var(%s%1d%1d)",ca,i,j);
10609: fprintf(ficparo," Var(%s%1d%1d)",ca,i,j);
10610: }else{
10611: printf(" 0.");
10612: fprintf(ficparo," 0.");
10613: }
10614: }
10615: }
10616: } /* end lk */
10617: } /* end lj */
10618: } /* end li */
10619: printf("\n");
10620: fprintf(ficparo,"\n");
10621: numlinepar++;
10622: } /* end k*/
10623: } /*end j */
10624: } /* end i */
10625: } /* end itimes */
10626:
10627: } /* end of prwizard */
10628: /******************* Gompertz Likelihood ******************************/
10629: double gompertz(double x[])
10630: {
1.302 brouard 10631: double A=0.0,B=0.,L=0.0,sump=0.,num=0.;
1.126 brouard 10632: int i,n=0; /* n is the size of the sample */
10633:
1.220 brouard 10634: for (i=1;i<=imx ; i++) {
1.126 brouard 10635: sump=sump+weight[i];
10636: /* sump=sump+1;*/
10637: num=num+1;
10638: }
1.302 brouard 10639: L=0.0;
10640: /* agegomp=AGEGOMP; */
1.126 brouard 10641: /* for (i=0; i<=imx; i++)
10642: if (wav[i]>0) printf("i=%d ageex=%lf agecens=%lf agedc=%lf cens=%d %d\n" ,i,ageexmed[i],agecens[i],agedc[i],cens[i],wav[i]);*/
10643:
1.302 brouard 10644: for (i=1;i<=imx ; i++) {
10645: /* mu(a)=mu(agecomp)*exp(teta*(age-agegomp))
10646: mu(a)=x[1]*exp(x[2]*(age-agegomp)); x[1] and x[2] are per year.
10647: * L= Product mu(agedeces)exp(-\int_ageexam^agedc mu(u) du ) for a death between agedc (in month)
10648: * and agedc +1 month, cens[i]=0: log(x[1]/YEARM)
10649: * +
10650: * exp(-\int_ageexam^agecens mu(u) du ) when censored, cens[i]=1
10651: */
10652: if (wav[i] > 1 || agedc[i] < AGESUP) {
10653: if (cens[i] == 1){
10654: A=-x[1]/(x[2])*(exp(x[2]*(agecens[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)));
10655: } else if (cens[i] == 0){
1.126 brouard 10656: A=-x[1]/(x[2])*(exp(x[2]*(agedc[i]-agegomp))-exp(x[2]*(ageexmed[i]-agegomp)))
1.302 brouard 10657: +log(x[1]/YEARM) +x[2]*(agedc[i]-agegomp)+log(YEARM);
10658: } else
10659: printf("Gompertz cens[%d] neither 1 nor 0\n",i);
1.126 brouard 10660: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
1.302 brouard 10661: L=L+A*weight[i];
1.126 brouard 10662: /* printf("\ni=%d A=%f L=%lf x[1]=%lf x[2]=%lf ageex=%lf agecens=%lf cens=%d agedc=%lf weight=%lf\n",i,A,L,x[1],x[2],ageexmed[i]*12,agecens[i]*12,cens[i],agedc[i]*12,weight[i]);*/
1.302 brouard 10663: }
10664: }
1.126 brouard 10665:
1.302 brouard 10666: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
1.126 brouard 10667:
10668: return -2*L*num/sump;
10669: }
10670:
1.136 brouard 10671: #ifdef GSL
10672: /******************* Gompertz_f Likelihood ******************************/
10673: double gompertz_f(const gsl_vector *v, void *params)
10674: {
1.302 brouard 10675: double A=0.,B=0.,LL=0.0,sump=0.,num=0.;
1.136 brouard 10676: double *x= (double *) v->data;
10677: int i,n=0; /* n is the size of the sample */
10678:
10679: for (i=0;i<=imx-1 ; i++) {
10680: sump=sump+weight[i];
10681: /* sump=sump+1;*/
10682: num=num+1;
10683: }
10684:
10685:
10686: /* for (i=0; i<=imx; i++)
10687: if (wav[i]>0) printf("i=%d ageex=%lf agecens=%lf agedc=%lf cens=%d %d\n" ,i,ageexmed[i],agecens[i],agedc[i],cens[i],wav[i]);*/
10688: printf("x[0]=%lf x[1]=%lf\n",x[0],x[1]);
10689: for (i=1;i<=imx ; i++)
10690: {
10691: if (cens[i] == 1 && wav[i]>1)
10692: A=-x[0]/(x[1])*(exp(x[1]*(agecens[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)));
10693:
10694: if (cens[i] == 0 && wav[i]>1)
10695: A=-x[0]/(x[1])*(exp(x[1]*(agedc[i]-agegomp))-exp(x[1]*(ageexmed[i]-agegomp)))
10696: +log(x[0]/YEARM)+x[1]*(agedc[i]-agegomp)+log(YEARM);
10697:
10698: /*if (wav[i] > 1 && agecens[i] > 15) {*/ /* ??? */
10699: if (wav[i] > 1 ) { /* ??? */
10700: LL=LL+A*weight[i];
10701: /* printf("\ni=%d A=%f L=%lf x[1]=%lf x[2]=%lf ageex=%lf agecens=%lf cens=%d agedc=%lf weight=%lf\n",i,A,L,x[1],x[2],ageexmed[i]*12,agecens[i]*12,cens[i],agedc[i]*12,weight[i]);*/
10702: }
10703: }
10704:
10705: /*printf("x1=%2.9f x2=%2.9f x3=%2.9f L=%f\n",x[1],x[2],x[3],L);*/
10706: printf("x[0]=%lf x[1]=%lf -2*LL*num/sump=%lf\n",x[0],x[1],-2*LL*num/sump);
10707:
10708: return -2*LL*num/sump;
10709: }
10710: #endif
10711:
1.126 brouard 10712: /******************* Printing html file ***********/
1.201 brouard 10713: void printinghtmlmort(char fileresu[], char title[], char datafile[], int firstpass, \
1.126 brouard 10714: int lastpass, int stepm, int weightopt, char model[],\
10715: int imx, double p[],double **matcov,double agemortsup){
10716: int i,k;
10717:
10718: fprintf(fichtm,"<ul><li><h4>Result files </h4>\n Force of mortality. Parameters of the Gompertz fit (with confidence interval in brackets):<br>");
10719: fprintf(fichtm," mu(age) =%lf*exp(%lf*(age-%d)) per year<br><br>",p[1],p[2],agegomp);
10720: for (i=1;i<=2;i++)
10721: fprintf(fichtm," p[%d] = %lf [%f ; %f]<br>\n",i,p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.199 brouard 10722: fprintf(fichtm,"<br><br><img src=\"graphmort.svg\">");
1.126 brouard 10723: fprintf(fichtm,"</ul>");
10724:
10725: fprintf(fichtm,"<ul><li><h4>Life table</h4>\n <br>");
10726:
10727: fprintf(fichtm,"\nAge l<inf>x</inf> q<inf>x</inf> d(x,x+1) L<inf>x</inf> T<inf>x</inf> e<infx</inf><br>");
10728:
10729: for (k=agegomp;k<(agemortsup-2);k++)
10730: fprintf(fichtm,"%d %.0lf %lf %.0lf %.0lf %.0lf %lf<br>\n",k,lsurv[k],p[1]*exp(p[2]*(k-agegomp)),(p[1]*exp(p[2]*(k-agegomp)))*lsurv[k],lpop[k],tpop[k],tpop[k]/lsurv[k]);
10731:
10732:
10733: fflush(fichtm);
10734: }
10735:
10736: /******************* Gnuplot file **************/
1.201 brouard 10737: void printinggnuplotmort(char fileresu[], char optionfilefiname[], double ageminpar, double agemaxpar, double fage , char pathc[], double p[]){
1.126 brouard 10738:
10739: char dirfileres[132],optfileres[132];
1.164 brouard 10740:
1.126 brouard 10741: int ng;
10742:
10743:
10744: /*#ifdef windows */
10745: fprintf(ficgp,"cd \"%s\" \n",pathc);
10746: /*#endif */
10747:
10748:
10749: strcpy(dirfileres,optionfilefiname);
10750: strcpy(optfileres,"vpl");
1.199 brouard 10751: fprintf(ficgp,"set out \"graphmort.svg\"\n ");
1.126 brouard 10752: fprintf(ficgp,"set xlabel \"Age\"\n set ylabel \"Force of mortality (per year)\" \n ");
1.199 brouard 10753: fprintf(ficgp, "set ter svg size 640, 480\n set log y\n");
1.145 brouard 10754: /* fprintf(ficgp, "set size 0.65,0.65\n"); */
1.126 brouard 10755: fprintf(ficgp,"plot [%d:100] %lf*exp(%lf*(x-%d))",agegomp,p[1],p[2],agegomp);
10756:
10757: }
10758:
1.136 brouard 10759: int readdata(char datafile[], int firstobs, int lastobs, int *imax)
10760: {
1.126 brouard 10761:
1.136 brouard 10762: /*-------- data file ----------*/
10763: FILE *fic;
10764: char dummy[]=" ";
1.240 brouard 10765: int i=0, j=0, n=0, iv=0, v;
1.223 brouard 10766: int lstra;
1.136 brouard 10767: int linei, month, year,iout;
1.302 brouard 10768: int noffset=0; /* This is the offset if BOM data file */
1.136 brouard 10769: char line[MAXLINE], linetmp[MAXLINE];
1.164 brouard 10770: char stra[MAXLINE], strb[MAXLINE];
1.136 brouard 10771: char *stratrunc;
1.223 brouard 10772:
1.349 brouard 10773: /* DummyV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
10774: /* FixedV=ivector(-1,NCOVMAX); /\* 1 to 3 *\/ */
1.339 brouard 10775:
10776: ncovcolt=ncovcol+nqv+ntv+nqtv; /* total of covariates in the data, not in the model equation */
10777:
1.136 brouard 10778: if((fic=fopen(datafile,"r"))==NULL) {
1.218 brouard 10779: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10780: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
1.136 brouard 10781: }
1.126 brouard 10782:
1.302 brouard 10783: /* Is it a BOM UTF-8 Windows file? */
10784: /* First data line */
10785: linei=0;
10786: while(fgets(line, MAXLINE, fic)) {
10787: noffset=0;
10788: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
10789: {
10790: noffset=noffset+3;
10791: printf("# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);fflush(stdout);
10792: fprintf(ficlog,"# Data file '%s' is an UTF8 BOM file, please convert to UTF8 or ascii file and rerun.\n",datafile);
10793: fflush(ficlog); return 1;
10794: }
10795: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
10796: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
10797: {
10798: noffset=noffset+2;
1.304 brouard 10799: printf("# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);fflush(stdout);
10800: fprintf(ficlog,"# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);
1.302 brouard 10801: fflush(ficlog); return 1;
10802: }
10803: else if( line[0] == 0 && line[1] == 0)
10804: {
10805: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
10806: noffset=noffset+4;
1.304 brouard 10807: printf("# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);fflush(stdout);
10808: fprintf(ficlog,"# Error Data file '%s' is a huge UTF16BE BOM file, please convert to UTF8 or ascii file (for example with dos2unix) and rerun.\n",datafile);
1.302 brouard 10809: fflush(ficlog); return 1;
10810: }
10811: } else{
10812: ;/*printf(" Not a BOM file\n");*/
10813: }
10814: /* If line starts with a # it is a comment */
10815: if (line[noffset] == '#') {
10816: linei=linei+1;
10817: break;
10818: }else{
10819: break;
10820: }
10821: }
10822: fclose(fic);
10823: if((fic=fopen(datafile,"r"))==NULL) {
10824: printf("Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(stdout);
10825: fprintf(ficlog,"Problem while opening datafile: %s with errno='%s'\n", datafile,strerror(errno));fflush(ficlog);return 1;
10826: }
10827: /* Not a Bom file */
10828:
1.136 brouard 10829: i=1;
10830: while ((fgets(line, MAXLINE, fic) != NULL) &&((i >= firstobs) && (i <=lastobs))) {
10831: linei=linei+1;
10832: for(j=strlen(line); j>=0;j--){ /* Untabifies line */
10833: if(line[j] == '\t')
10834: line[j] = ' ';
10835: }
10836: for(j=strlen(line)-1; (line[j]==' ')||(line[j]==10)||(line[j]==13);j--){
10837: ;
10838: };
10839: line[j+1]=0; /* Trims blanks at end of line */
10840: if(line[0]=='#'){
10841: fprintf(ficlog,"Comment line\n%s\n",line);
10842: printf("Comment line\n%s\n",line);
10843: continue;
10844: }
10845: trimbb(linetmp,line); /* Trims multiple blanks in line */
1.164 brouard 10846: strcpy(line, linetmp);
1.223 brouard 10847:
10848: /* Loops on waves */
10849: for (j=maxwav;j>=1;j--){
10850: for (iv=nqtv;iv>=1;iv--){ /* Loop on time varying quantitative variables */
1.238 brouard 10851: cutv(stra, strb, line, ' ');
10852: if(strb[0]=='.') { /* Missing value */
10853: lval=-1;
10854: cotqvar[j][iv][i]=-1; /* 0.0/0.0 */
1.341 brouard 10855: cotvar[j][ncovcol+nqv+ntv+iv][i]=-1; /* For performance reasons */
1.238 brouard 10856: if(isalpha(strb[1])) { /* .m or .d Really Missing value */
10857: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value out of %d measured at wave %d. If missing, you should remove this individual or impute a value. Exiting.\n", strb, linei,i,line,iv, nqtv, j);
10858: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value out of %d measured at wave %d. If missing, you should remove this individual or impute a value. Exiting.\n", strb, linei,i,line,iv, nqtv, j);fflush(ficlog);
10859: return 1;
10860: }
10861: }else{
10862: errno=0;
10863: /* what_kind_of_number(strb); */
10864: dval=strtod(strb,&endptr);
10865: /* if( strb[0]=='\0' || (*endptr != '\0')){ */
10866: /* if(strb != endptr && *endptr == '\0') */
10867: /* dval=dlval; */
10868: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
10869: if( strb[0]=='\0' || (*endptr != '\0')){
10870: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value out of %d measured at wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,iv, nqtv, j,maxwav);
10871: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value out of %d measured at wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line, iv, nqtv, j,maxwav);fflush(ficlog);
10872: return 1;
10873: }
10874: cotqvar[j][iv][i]=dval;
1.341 brouard 10875: cotvar[j][ncovcol+nqv+ntv+iv][i]=dval; /* because cotvar starts now at first ntv */
1.238 brouard 10876: }
10877: strcpy(line,stra);
1.223 brouard 10878: }/* end loop ntqv */
1.225 brouard 10879:
1.223 brouard 10880: for (iv=ntv;iv>=1;iv--){ /* Loop on time varying dummies */
1.238 brouard 10881: cutv(stra, strb, line, ' ');
10882: if(strb[0]=='.') { /* Missing value */
10883: lval=-1;
10884: }else{
10885: errno=0;
10886: lval=strtol(strb,&endptr,10);
10887: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
10888: if( strb[0]=='\0' || (*endptr != '\0')){
10889: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th dummy covariate out of %d measured at wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,iv, ntv, j,maxwav);
10890: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d dummy covariate out of %d measured wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,iv, ntv,j,maxwav);fflush(ficlog);
10891: return 1;
10892: }
10893: }
10894: if(lval <-1 || lval >1){
10895: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10896: Should be a value of %d(nth) covariate of wave %d (0 should be the value for the reference and 1\n \
1.223 brouard 10897: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10898: For example, for multinomial values like 1, 2 and 3,\n \
10899: build V1=0 V2=0 for the reference value (1),\n \
10900: V1=1 V2=0 for (2) \n \
1.223 brouard 10901: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10902: output of IMaCh is often meaningless.\n \
1.319 brouard 10903: Exiting.\n",lval,linei, i,line,iv,j);
1.238 brouard 10904: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.319 brouard 10905: Should be a value of %d(nth) covariate of wave %d (0 should be the value for the reference and 1\n \
1.223 brouard 10906: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.238 brouard 10907: For example, for multinomial values like 1, 2 and 3,\n \
10908: build V1=0 V2=0 for the reference value (1),\n \
10909: V1=1 V2=0 for (2) \n \
1.223 brouard 10910: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.238 brouard 10911: output of IMaCh is often meaningless.\n \
1.319 brouard 10912: Exiting.\n",lval,linei, i,line,iv,j);fflush(ficlog);
1.238 brouard 10913: return 1;
10914: }
1.341 brouard 10915: cotvar[j][ncovcol+nqv+iv][i]=(double)(lval);
1.238 brouard 10916: strcpy(line,stra);
1.223 brouard 10917: }/* end loop ntv */
1.225 brouard 10918:
1.223 brouard 10919: /* Statuses at wave */
1.137 brouard 10920: cutv(stra, strb, line, ' ');
1.223 brouard 10921: if(strb[0]=='.') { /* Missing value */
1.238 brouard 10922: lval=-1;
1.136 brouard 10923: }else{
1.238 brouard 10924: errno=0;
10925: lval=strtol(strb,&endptr,10);
10926: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN))*/
1.347 brouard 10927: if( strb[0]=='\0' || (*endptr != '\0' )){
10928: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a status of wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,j,maxwav);
10929: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a status of wave %d. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line,j,maxwav);fflush(ficlog);
10930: return 1;
10931: }else if( lval==0 || lval > nlstate+ndeath){
1.348 brouard 10932: printf("Error in data around '%s' at line number %d for individual %d, '%s'\n Should be a state at wave %d. A state should be 1 to %d and not %ld.\n Fix your data file '%s'! Exiting.\n", strb, linei,i,line,j,nlstate+ndeath, lval, datafile);fflush(stdout);
10933: fprintf(ficlog,"Error in data around '%s' at line number %d for individual %d, '%s'\n Should be a state at wave %d. A state should be 1 to %d and not %ld.\n Fix your data file '%s'! Exiting.\n", strb, linei,i,line,j,nlstate+ndeath, lval, datafile); fflush(ficlog);
1.238 brouard 10934: return 1;
10935: }
1.136 brouard 10936: }
1.225 brouard 10937:
1.136 brouard 10938: s[j][i]=lval;
1.225 brouard 10939:
1.223 brouard 10940: /* Date of Interview */
1.136 brouard 10941: strcpy(line,stra);
10942: cutv(stra, strb,line,' ');
1.169 brouard 10943: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10944: }
1.169 brouard 10945: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.225 brouard 10946: month=99;
10947: year=9999;
1.136 brouard 10948: }else{
1.225 brouard 10949: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of interview (mm/yyyy or .) at wave %d. Exiting.\n",strb, linei,i, line,j);
10950: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of interview (mm/yyyy or .) at wave %d. Exiting.\n",strb, linei,i, line,j);fflush(ficlog);
10951: return 1;
1.136 brouard 10952: }
10953: anint[j][i]= (double) year;
1.302 brouard 10954: mint[j][i]= (double)month;
10955: /* if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){ */
10956: /* printf("Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, mint[j][i],anint[j][i], moisnais[i],annais[i]); */
10957: /* fprintf(ficlog,"Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, mint[j][i],anint[j][i], moisnais[i],annais[i]); */
10958: /* } */
1.136 brouard 10959: strcpy(line,stra);
1.223 brouard 10960: } /* End loop on waves */
1.225 brouard 10961:
1.223 brouard 10962: /* Date of death */
1.136 brouard 10963: cutv(stra, strb,line,' ');
1.169 brouard 10964: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10965: }
1.169 brouard 10966: else if( (iout=sscanf(strb,"%s.",dummy)) != 0){
1.136 brouard 10967: month=99;
10968: year=9999;
10969: }else{
1.141 brouard 10970: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of death (mm/yyyy or .). Exiting.\n",strb, linei,i,line);
1.225 brouard 10971: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of death (mm/yyyy or .). Exiting.\n",strb, linei,i,line);fflush(ficlog);
10972: return 1;
1.136 brouard 10973: }
10974: andc[i]=(double) year;
10975: moisdc[i]=(double) month;
10976: strcpy(line,stra);
10977:
1.223 brouard 10978: /* Date of birth */
1.136 brouard 10979: cutv(stra, strb,line,' ');
1.169 brouard 10980: if( (iout=sscanf(strb,"%d/%d",&month, &year)) != 0){
1.136 brouard 10981: }
1.169 brouard 10982: else if( (iout=sscanf(strb,"%s.", dummy)) != 0){
1.136 brouard 10983: month=99;
10984: year=9999;
10985: }else{
1.141 brouard 10986: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of birth (mm/yyyy or .). Exiting.\n",strb, linei,i,line);
10987: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of birth (mm/yyyy or .). Exiting.\n",strb, linei,i,line);fflush(ficlog);
1.225 brouard 10988: return 1;
1.136 brouard 10989: }
10990: if (year==9999) {
1.141 brouard 10991: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of birth (mm/yyyy) but at least the year of birth should be given. Exiting.\n",strb, linei,i,line);
10992: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be a date of birth (mm/yyyy) but at least the year of birth should be given. Exiting.\n",strb, linei,i,line);fflush(ficlog);
1.225 brouard 10993: return 1;
10994:
1.136 brouard 10995: }
10996: annais[i]=(double)(year);
1.302 brouard 10997: moisnais[i]=(double)(month);
10998: for (j=1;j<=maxwav;j++){
10999: if( (int)anint[j][i]+ (int)(mint[j][i])/12. < (int) (moisnais[i]/12.+annais[i])){
11000: printf("Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, (int)mint[j][i],(int)anint[j][i], j,(int)moisnais[i],(int)annais[i]);
11001: fprintf(ficlog,"Warning reading data around '%s' at line number %d for individual %d, '%s'\nThe date of interview (%2d/%4d) at wave %d occurred before the date of birth (%2d/%4d).\n",strb, linei,i, line, (int)mint[j][i],(int)anint[j][i], j, (int)moisnais[i],(int)annais[i]);
11002: }
11003: }
11004:
1.136 brouard 11005: strcpy(line,stra);
1.225 brouard 11006:
1.223 brouard 11007: /* Sample weight */
1.136 brouard 11008: cutv(stra, strb,line,' ');
11009: errno=0;
11010: dval=strtod(strb,&endptr);
11011: if( strb[0]=='\0' || (*endptr != '\0')){
1.141 brouard 11012: printf("Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
11013: fprintf(ficlog,"Error reading data around '%f' at line number %d, \"%s\" for individual %d\nShould be a weight. Exiting.\n",dval, i,line,linei);
1.136 brouard 11014: fflush(ficlog);
11015: return 1;
11016: }
11017: weight[i]=dval;
11018: strcpy(line,stra);
1.225 brouard 11019:
1.223 brouard 11020: for (iv=nqv;iv>=1;iv--){ /* Loop on fixed quantitative variables */
11021: cutv(stra, strb, line, ' ');
11022: if(strb[0]=='.') { /* Missing value */
1.225 brouard 11023: lval=-1;
1.311 brouard 11024: coqvar[iv][i]=NAN;
11025: covar[ncovcol+iv][i]=NAN; /* including qvar in standard covar for performance reasons */
1.223 brouard 11026: }else{
1.225 brouard 11027: errno=0;
11028: /* what_kind_of_number(strb); */
11029: dval=strtod(strb,&endptr);
11030: /* if(strb != endptr && *endptr == '\0') */
11031: /* dval=dlval; */
11032: /* if (errno == ERANGE && (lval == LONG_MAX || lval == LONG_MIN)) */
11033: if( strb[0]=='\0' || (*endptr != '\0')){
11034: printf("Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value (out of %d) constant for all waves. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line, iv, nqv, maxwav);
11035: fprintf(ficlog,"Error reading data around '%s' at line number %d for individual %d, '%s'\nShould be the %d th quantitative value (out of %d) constant for all waves. Setting maxwav=%d might be wrong. Exiting.\n", strb, linei,i,line, iv, nqv, maxwav);fflush(ficlog);
11036: return 1;
11037: }
11038: coqvar[iv][i]=dval;
1.226 brouard 11039: covar[ncovcol+iv][i]=dval; /* including qvar in standard covar for performance reasons */
1.223 brouard 11040: }
11041: strcpy(line,stra);
11042: }/* end loop nqv */
1.136 brouard 11043:
1.223 brouard 11044: /* Covariate values */
1.136 brouard 11045: for (j=ncovcol;j>=1;j--){
11046: cutv(stra, strb,line,' ');
1.223 brouard 11047: if(strb[0]=='.') { /* Missing covariate value */
1.225 brouard 11048: lval=-1;
1.136 brouard 11049: }else{
1.225 brouard 11050: errno=0;
11051: lval=strtol(strb,&endptr,10);
11052: if( strb[0]=='\0' || (*endptr != '\0')){
11053: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\nShould be a covariate value (=0 for the reference or 1 for alternative). Exiting.\n",lval, linei,i, line);
11054: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\nShould be a covariate value (=0 for the reference or 1 for alternative). Exiting.\n",lval, linei,i, line);fflush(ficlog);
11055: return 1;
11056: }
1.136 brouard 11057: }
11058: if(lval <-1 || lval >1){
1.225 brouard 11059: printf("Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11060: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11061: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11062: For example, for multinomial values like 1, 2 and 3,\n \
11063: build V1=0 V2=0 for the reference value (1),\n \
11064: V1=1 V2=0 for (2) \n \
1.136 brouard 11065: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11066: output of IMaCh is often meaningless.\n \
1.136 brouard 11067: Exiting.\n",lval,linei, i,line,j);
1.225 brouard 11068: fprintf(ficlog,"Error reading data around '%ld' at line number %d for individual %d, '%s'\n \
1.136 brouard 11069: Should be a value of %d(nth) covariate (0 should be the value for the reference and 1\n \
11070: for the alternative. IMaCh does not build design variables automatically, do it yourself.\n \
1.225 brouard 11071: For example, for multinomial values like 1, 2 and 3,\n \
11072: build V1=0 V2=0 for the reference value (1),\n \
11073: V1=1 V2=0 for (2) \n \
1.136 brouard 11074: and V1=0 V2=1 for (3). V1=1 V2=1 should not exist and the corresponding\n \
1.225 brouard 11075: output of IMaCh is often meaningless.\n \
1.136 brouard 11076: Exiting.\n",lval,linei, i,line,j);fflush(ficlog);
1.225 brouard 11077: return 1;
1.136 brouard 11078: }
11079: covar[j][i]=(double)(lval);
11080: strcpy(line,stra);
11081: }
11082: lstra=strlen(stra);
1.225 brouard 11083:
1.136 brouard 11084: if(lstra > 9){ /* More than 2**32 or max of what printf can write with %ld */
11085: stratrunc = &(stra[lstra-9]);
11086: num[i]=atol(stratrunc);
11087: }
11088: else
11089: num[i]=atol(stra);
11090: /*if((s[2][i]==2) && (s[3][i]==-1)&&(s[4][i]==9)){
11091: printf("%ld %.lf %.lf %.lf %.lf/%.lf %.lf/%.lf %.lf/%.lf %d %.lf/%.lf %d %.lf/%.lf %d %.lf/%.lf %d\n",num[i],(covar[1][i]), (covar[2][i]),weight[i], (moisnais[i]), (annais[i]), (moisdc[i]), (andc[i]), (mint[1][i]), (anint[1][i]), (s[1][i]), (mint[2][i]), (anint[2][i]), (s[2][i]), (mint[3][i]), (anint[3][i]), (s[3][i]), (mint[4][i]), (anint[4][i]), (s[4][i])); ij=ij+1;}*/
11092:
11093: i=i+1;
11094: } /* End loop reading data */
1.225 brouard 11095:
1.136 brouard 11096: *imax=i-1; /* Number of individuals */
11097: fclose(fic);
1.225 brouard 11098:
1.136 brouard 11099: return (0);
1.164 brouard 11100: /* endread: */
1.225 brouard 11101: printf("Exiting readdata: ");
11102: fclose(fic);
11103: return (1);
1.223 brouard 11104: }
1.126 brouard 11105:
1.234 brouard 11106: void removefirstspace(char **stri){/*, char stro[]) {*/
1.230 brouard 11107: char *p1 = *stri, *p2 = *stri;
1.235 brouard 11108: while (*p2 == ' ')
1.234 brouard 11109: p2++;
11110: /* while ((*p1++ = *p2++) !=0) */
11111: /* ; */
11112: /* do */
11113: /* while (*p2 == ' ') */
11114: /* p2++; */
11115: /* while (*p1++ == *p2++); */
11116: *stri=p2;
1.145 brouard 11117: }
11118:
1.330 brouard 11119: int decoderesult( char resultline[], int nres)
1.230 brouard 11120: /**< This routine decode one result line and returns the combination # of dummy covariates only **/
11121: {
1.235 brouard 11122: int j=0, k=0, k1=0, k2=0, k3=0, k4=0, match=0, k2q=0, k3q=0, k4q=0;
1.230 brouard 11123: char resultsav[MAXLINE];
1.330 brouard 11124: /* int resultmodel[MAXLINE]; */
1.334 brouard 11125: /* int modelresult[MAXLINE]; */
1.230 brouard 11126: char stra[80], strb[80], strc[80], strd[80],stre[80];
11127:
1.234 brouard 11128: removefirstspace(&resultline);
1.332 brouard 11129: printf("decoderesult:%s\n",resultline);
1.230 brouard 11130:
1.332 brouard 11131: strcpy(resultsav,resultline);
1.342 brouard 11132: /* printf("Decoderesult resultsav=\"%s\" resultline=\"%s\"\n", resultsav, resultline); */
1.230 brouard 11133: if (strlen(resultsav) >1){
1.334 brouard 11134: j=nbocc(resultsav,'='); /**< j=Number of covariate values'=' in this resultline */
1.230 brouard 11135: }
1.353 brouard 11136: if(j == 0 && cptcovs== 0){ /* Resultline but no = and no covariate in the model */
1.253 brouard 11137: TKresult[nres]=0; /* Combination for the nresult and the model */
11138: return (0);
11139: }
1.234 brouard 11140: if( j != cptcovs ){ /* Be careful if a variable is in a product but not single */
1.353 brouard 11141: fprintf(ficlog,"ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, 1+age+%s.\n",j, cptcovs, model);fflush(ficlog);
11142: printf("ERROR: the number of variables in the resultline which is %d, differs from the number %d of single variables used in the model line, 1+age+%s.\n",j, cptcovs, model);fflush(stdout);
11143: if(j==0)
11144: return 1;
1.234 brouard 11145: }
1.334 brouard 11146: for(k=1; k<=j;k++){ /* Loop on any covariate of the RESULT LINE */
1.234 brouard 11147: if(nbocc(resultsav,'=') >1){
1.318 brouard 11148: cutl(stra,strb,resultsav,' '); /* keeps in strb after the first ' ' (stra is the rest of the resultline to be analyzed in the next loop *//* resultsav= "V4=1 V5=25.1 V3=0" stra= "V5=25.1 V3=0" strb= "V4=1" */
1.332 brouard 11149: /* If resultsav= "V4= 1 V5=25.1 V3=0" with a blank then strb="V4=" and stra="1 V5=25.1 V3=0" */
1.318 brouard 11150: cutl(strc,strd,strb,'='); /* strb:"V4=1" strc="1" strd="V4" */
1.332 brouard 11151: /* If a blank, then strc="V4=" and strd='\0' */
11152: if(strc[0]=='\0'){
11153: printf("Error in resultline, probably a blank after the \"%s\", \"result:%s\", stra=\"%s\" resultsav=\"%s\"\n",strb,resultline, stra, resultsav);
11154: fprintf(ficlog,"Error in resultline, probably a blank after the \"V%s=\", resultline=%s\n",strb,resultline);
11155: return 1;
11156: }
1.234 brouard 11157: }else
11158: cutl(strc,strd,resultsav,'=');
1.318 brouard 11159: Tvalsel[k]=atof(strc); /* 1 */ /* Tvalsel of k is the float value of the kth covariate appearing in this result line */
1.234 brouard 11160:
1.230 brouard 11161: cutl(strc,stre,strd,'V'); /* strd='V4' strc=4 stre='V' */;
1.318 brouard 11162: Tvarsel[k]=atoi(strc); /* 4 */ /* Tvarsel is the id of the kth covariate in the result line Tvarsel[1] in "V4=1.." is 4.*/
1.230 brouard 11163: /* Typevarsel[k]=1; /\* 1 for age product *\/ */
11164: /* cptcovsel++; */
11165: if (nbocc(stra,'=') >0)
11166: strcpy(resultsav,stra); /* and analyzes it */
11167: }
1.235 brouard 11168: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11169: /* Feeds resultmodel[nres][k1]=k2 for k1th product covariate with age in the model equation fed by the index k2 of the resutline*/
1.334 brouard 11170: for(k1=1; k1<= cptcovt ;k1++){ /* Loop on MODEL LINE V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.332 brouard 11171: if(Typevar[k1]==0){ /* Single covariate in model */
11172: /* 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product */
1.234 brouard 11173: match=0;
1.318 brouard 11174: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11175: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11176: modelresult[nres][k2]=k1;/* modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.318 brouard 11177: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
1.234 brouard 11178: break;
11179: }
11180: }
11181: if(match == 0){
1.338 brouard 11182: printf("Error in result line (Dummy single): V%d is missing in result: %s according to model=1+age+%s. Tvar[k1=%d]=%d is different from Tvarsel[k2=%d]=%d.\n",Tvar[k1], resultline, model,k1, Tvar[k1], k2, Tvarsel[k2]);
11183: fprintf(ficlog,"Error in result line (Dummy single): V%d is missing in result: %s according to model=1+age+%s\n",Tvar[k1], resultline, model);
1.310 brouard 11184: return 1;
1.234 brouard 11185: }
1.332 brouard 11186: }else if(Typevar[k1]==1){ /* Product with age We want to get the position k2 in the resultline of the product k1 in the model line*/
11187: /* We feed resultmodel[k1]=k2; */
11188: match=0;
11189: for(k2=1; k2 <=j;k2++){/* Loop on resultline. jth occurence of = signs in the result line. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11190: if(Tvar[k1]==Tvarsel[k2]) {/* Tvar is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
1.334 brouard 11191: modelresult[nres][k2]=k1;/* we found a Vn=1 corrresponding to Vn*age in the model modelresult[2]=1 modelresult[1]=2 modelresult[3]=3 modelresult[6]=4 modelresult[9]=5 */
1.332 brouard 11192: resultmodel[nres][k1]=k2; /* Added here */
1.342 brouard 11193: /* printf("Decoderesult first modelresult[k2=%d]=%d (k1) V%d*AGE\n",k2,k1,Tvar[k1]); */
1.332 brouard 11194: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11195: break;
11196: }
11197: }
11198: if(match == 0){
1.338 brouard 11199: printf("Error in result line (Product with age): V%d is missing in result: %s according to model=1+age+%s (Tvarsel[k2=%d]=%d)\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]);
11200: fprintf(ficlog,"Error in result line (Product with age): V%d is missing in result: %s according to model=1+age+%s (Tvarsel[k2=%d]=%d)\n",Tvar[k1], resultline, model, k2, Tvarsel[k2]);
1.332 brouard 11201: return 1;
11202: }
1.349 brouard 11203: }else if(Typevar[k1]==2 || Typevar[k1]==3){ /* Product with or without age. We want to get the position in the resultline of the product in the model line*/
1.332 brouard 11204: /* resultmodel[nres][of such a Vn * Vm product k1] is not unique, so can't exist, we feed Tvard[k1][1] and [2] */
11205: match=0;
1.342 brouard 11206: /* printf("Decoderesult very first Product Tvardk[k1=%d][1]=%d Tvardk[k1=%d][2]=%d V%d * V%d\n",k1,Tvardk[k1][1],k1,Tvardk[k1][2],Tvardk[k1][1],Tvardk[k1][2]); */
1.332 brouard 11207: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11208: if(Tvardk[k1][1]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11209: /* modelresult[k2]=k1; */
1.342 brouard 11210: /* printf("Decoderesult first Product modelresult[k2=%d]=%d (k1) V%d * \n",k2,k1,Tvarsel[k2]); */
1.332 brouard 11211: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11212: }
11213: }
11214: if(match == 0){
1.349 brouard 11215: printf("Error in result line (Product without age first variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
11216: fprintf(ficlog,"Error in result line (Product without age first variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][1], resultline, model);
1.332 brouard 11217: return 1;
11218: }
11219: match=0;
11220: for(k2=1; k2 <=j;k2++){/* Loop on resultline. In result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
11221: if(Tvardk[k1][2]==Tvarsel[k2]) {/* Tvardk is coming from the model, Tvarsel from the result. Tvar[1]=5 == Tvarsel[2]=5 */
11222: /* modelresult[k2]=k1;*/
1.342 brouard 11223: /* printf("Decoderesult second Product modelresult[k2=%d]=%d (k1) * V%d \n ",k2,k1,Tvarsel[k2]); */
1.332 brouard 11224: match=1; /* modelresult of k2 variable of resultline is identical to k1 variable of the model good */
11225: break;
11226: }
11227: }
11228: if(match == 0){
1.349 brouard 11229: printf("Error in result line (Product without age second variable or double product with age): V%d is missing in result: %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
11230: fprintf(ficlog,"Error in result line (Product without age second variable or double product with age): V%d is missing in result : %s according to model=1+age+%s\n",Tvardk[k1][2], resultline, model);
1.332 brouard 11231: return 1;
11232: }
11233: }/* End of testing */
1.333 brouard 11234: }/* End loop cptcovt */
1.235 brouard 11235: /* Checking for missing or useless values in comparison of current model needs */
1.332 brouard 11236: /* Feeds resultmodel[nres][k1]=k2 for single covariate (k1) in the model equation */
1.334 brouard 11237: for(k2=1; k2 <=j;k2++){ /* j or cptcovs is the number of single covariates used either in the model line as well as in the result line (dummy or quantitative)
11238: * Loop on resultline variables: result line V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.234 brouard 11239: match=0;
1.318 brouard 11240: for(k1=1; k1<= cptcovt ;k1++){ /* loop on model: model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.332 brouard 11241: if(Typevar[k1]==0){ /* Single only */
1.349 brouard 11242: if(Tvar[k1]==Tvarsel[k2]) { /* Tvar[2]=4 == Tvarsel[1]=4 What if a product? */
1.330 brouard 11243: resultmodel[nres][k1]=k2; /* k1th position in the model equation corresponds to k2th position in the result line. resultmodel[2]=1 resultmodel[1]=2 resultmodel[3]=3 resultmodel[6]=4 resultmodel[9]=5 */
1.334 brouard 11244: modelresult[nres][k2]=k1; /* k1th position in the model equation corresponds to k2th position in the result line. modelresult[1]=2 modelresult[2]=1 modelresult[3]=3 remodelresult[4]=6 modelresult[5]=9 */
1.234 brouard 11245: ++match;
11246: }
11247: }
11248: }
11249: if(match == 0){
1.338 brouard 11250: printf("Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
11251: fprintf(ficlog,"Error in result line: variable V%d is missing in model; result: %s, model=1+age+%s\n",Tvarsel[k2], resultline, model);
1.310 brouard 11252: return 1;
1.234 brouard 11253: }else if(match > 1){
1.338 brouard 11254: printf("Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
11255: fprintf(ficlog,"Error in result line: %d doubled; result: %s, model=1+age+%s\n",k2, resultline, model);
1.310 brouard 11256: return 1;
1.234 brouard 11257: }
11258: }
1.334 brouard 11259: /* cptcovres=j /\* Number of variables in the resultline is equal to cptcovs and thus useless *\/ */
1.234 brouard 11260: /* We need to deduce which combination number is chosen and save quantitative values */
1.235 brouard 11261: /* model line V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.330 brouard 11262: /* nres=1st result line: V4=1 V5=25.1 V3=0 V2=8 V1=1 */
11263: /* should correspond to the combination 6 of dummy: V4=1, V3=0, V1=1 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 1*1 + 0*2 + 1*4 = 5 + (1offset) = 6*/
11264: /* nres=2nd result line: V4=1 V5=24.1 V3=1 V2=8 V1=0 */
1.235 brouard 11265: /* should give a combination of dummy V4=1, V3=1, V1=0 => V4*2**(0) + V3*2**(1) + V1*2**(2) = 3 + (1offset) = 4*/
11266: /* 1 0 0 0 */
11267: /* 2 1 0 0 */
11268: /* 3 0 1 0 */
1.330 brouard 11269: /* 4 1 1 0 */ /* V4=1, V3=1, V1=0 (nres=2)*/
1.235 brouard 11270: /* 5 0 0 1 */
1.330 brouard 11271: /* 6 1 0 1 */ /* V4=1, V3=0, V1=1 (nres=1)*/
1.235 brouard 11272: /* 7 0 1 1 */
11273: /* 8 1 1 1 */
1.237 brouard 11274: /* V(Tvresult)=Tresult V4=1 V3=0 V1=1 Tresult[nres=1][2]=0 */
11275: /* V(Tvqresult)=Tqresult V5=25.1 V2=8 Tqresult[nres=1][1]=25.1 */
11276: /* V5*age V5 known which value for nres? */
11277: /* Tqinvresult[2]=8 Tqinvresult[1]=25.1 */
1.334 brouard 11278: for(k1=1, k=0, k4=0, k4q=0; k1 <=cptcovt;k1++){ /* cptcovt number of covariates (excluding 1 and age or age*age) in the MODEL equation.
11279: * loop on position k1 in the MODEL LINE */
1.331 brouard 11280: /* k counting number of combination of single dummies in the equation model */
11281: /* k4 counting single dummies in the equation model */
11282: /* k4q counting single quantitatives in the equation model */
1.344 brouard 11283: if( Dummy[k1]==0 && Typevar[k1]==0 ){ /* Dummy and Single, fixed or timevarying, k1 is sorting according to MODEL, but k3 to resultline */
1.334 brouard 11284: /* k4+1= (not always if quant in model) position in the resultline V(Tvarsel)=Tvalsel=Tresult[nres][pos](value); V(Tvresult[nres][pos] (variable): V(variable)=value) */
1.332 brouard 11285: /* modelresult[k3]=k1: k3th position in the result line corresponds to the k1 position in the model line (doesn't work with products)*/
1.330 brouard 11286: /* Value in the (current nres) resultline of the variable at the k1th position in the model equation resultmodel[nres][k1]= k3 */
1.332 brouard 11287: /* resultmodel[nres][k1]=k3: k1th position in the model correspond to the k3 position in the resultline */
11288: /* k3 is the position in the nres result line of the k1th variable of the model equation */
11289: /* Tvarsel[k3]: Name of the variable at the k3th position in the result line. */
11290: /* Tvalsel[k3]: Value of the variable at the k3th position in the result line. */
11291: /* Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline */
1.334 brouard 11292: /* Tvresult[nres][result_position]= name of the dummy variable at the result_position in the nres resultline */
1.332 brouard 11293: /* Tinvresult[nres][Name of a dummy variable]= value of the variable in the result line */
1.330 brouard 11294: /* TinvDoQresult[nres][Name of a Dummy or Q variable]= value of the variable in the result line */
1.332 brouard 11295: k3= resultmodel[nres][k1]; /* From position k1 in model get position k3 in result line */
11296: /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11297: k2=(int)Tvarsel[k3]; /* from position k3 in resultline get name k2: nres=1 k1=2=>k3=1 Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 (V4); k1=3=>k3=2 Tvarsel[2]=3 (V3)*/
1.330 brouard 11298: k+=Tvalsel[k3]*pow(2,k4); /* nres=1 k1=2 Tvalsel[1]=1 (V4=1); k1=3 k3=2 Tvalsel[2]=0 (V3=0) */
1.334 brouard 11299: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][Name]=Value; stores the value into the name of the variable. */
1.332 brouard 11300: /* Tinvresult[nres][4]=1 */
1.334 brouard 11301: /* Tresult[nres][k4+1]=Tvalsel[k3];/\* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) *\/ */
11302: Tresult[nres][k3]=Tvalsel[k3];/* Tresult[nres=2][1]=1(V4=1) Tresult[nres=2][2]=0(V3=0) */
11303: /* Tvresult[nres][k4+1]=(int)Tvarsel[k3];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11304: Tvresult[nres][k3]=(int)Tvarsel[k3];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
1.237 brouard 11305: Tinvresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* Tinvresult[nres][4]=1 */
1.334 brouard 11306: precov[nres][k1]=Tvalsel[k3]; /* Value from resultline of the variable at the k1 position in the model */
1.342 brouard 11307: /* printf("Decoderesult Dummy k=%d, k1=%d precov[nres=%d][k1=%d]=%.f V(k2=V%d)= Tvalsel[%d]=%d, 2**(%d)\n",k, k1, nres, k1,precov[nres][k1], k2, k3, (int)Tvalsel[k3], k4); */
1.235 brouard 11308: k4++;;
1.331 brouard 11309: }else if( Dummy[k1]==1 && Typevar[k1]==0 ){ /* Quantitative and single */
1.330 brouard 11310: /* Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
1.332 brouard 11311: /* Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline */
1.330 brouard 11312: /* Tqinvresult[nres][Name of a quantitative variable]= value of the variable in the result line */
1.332 brouard 11313: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 5 =k3q */
11314: k2q=(int)Tvarsel[k3q]; /* Name of variable at k3q th position in the resultline */
11315: /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
1.334 brouard 11316: /* Tqresult[nres][k4q+1]=Tvalsel[k3q]; /\* Tqresult[nres][1]=25.1 *\/ */
11317: /* Tvresult[nres][k4q+1]=(int)Tvarsel[k3q];/\* Tvresult[nres][1]=4 Tvresult[nres][3]=1 *\/ */
11318: /* Tvqresult[nres][k4q+1]=(int)Tvarsel[k3q]; /\* Tvqresult[nres][1]=5 *\/ */
11319: Tqresult[nres][k3q]=Tvalsel[k3q]; /* Tqresult[nres][1]=25.1 */
11320: Tvresult[nres][k3q]=(int)Tvarsel[k3q];/* Tvresult[nres][1]=4 Tvresult[nres][3]=1 */
11321: Tvqresult[nres][k3q]=(int)Tvarsel[k3q]; /* Tvqresult[nres][1]=5 */
1.237 brouard 11322: Tqinvresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.330 brouard 11323: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* Tqinvresult[nres][5]=25.1 */
1.332 brouard 11324: precov[nres][k1]=Tvalsel[k3q];
1.342 brouard 11325: /* printf("Decoderesult Quantitative nres=%d,precov[nres=%d][k1=%d]=%.f V(k2q=V%d)= Tvalsel[%d]=%d, Tvarsel[%d]=%f\n",nres, nres, k1,precov[nres][k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]); */
1.235 brouard 11326: k4q++;;
1.350 brouard 11327: }else if( Dummy[k1]==2 ){ /* For dummy with age product "V2+V3+V4+V6+V7+V6*V2+V7*V2+V6*V3+V7*V3+V6*V4+V7*V4+age*V2+age*V3+age*V4+age*V6+age*V7+age*V6*V2+age*V6*V3+age*V7*V3+age*V6*V4+age*V7*V4\r"*/
11328: /* Tvar[k1]; */ /* Age variable */ /* 17 age*V6*V2 ?*/
1.332 brouard 11329: /* Wrong we want the value of variable name Tvar[k1] */
1.350 brouard 11330: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
11331: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
11332: /* printf("Decoderesult Quantitative or Dummy (not with age) nres=%d k1=%d precov[nres=%d][k1=%d]=%.f V%d(=%.f) * V%d(=%.f) \n",nres, k1, nres, k1,precov[nres][k1], Tvardk[k1][1], TinvDoQresult[nres][Tvardk[k1][1]], Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][2]]); */
11333: }else{
11334: k3= resultmodel[nres][k1]; /* nres=1 k1=2 resultmodel[2(V4)] = 1=k3 ; k1=3 resultmodel[3(V3)] = 2=k3*/
11335: k2=(int)Tvarsel[k3]; /* nres=1 k1=2=>k3=1 Tvarsel[resultmodel[2]]= Tvarsel[1] = 4=k2 (V4); k1=3=>k3=2 Tvarsel[2]=3 (V3)*/
11336: TinvDoQresult[nres][(int)Tvarsel[k3]]=Tvalsel[k3]; /* TinvDoQresult[nres][4]=1 */
11337: precov[nres][k1]=Tvalsel[k3];
11338: }
1.342 brouard 11339: /* printf("Decoderesult Dummy with age k=%d, k1=%d precov[nres=%d][k1=%d]=%.f Tvar[%d]=V%d k2=Tvarsel[%d]=%d Tvalsel[%d]=%d\n",k, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k3,(int)Tvarsel[k3], k3, (int)Tvalsel[k3]); */
1.331 brouard 11340: }else if( Dummy[k1]==3 ){ /* For quant with age product */
1.350 brouard 11341: if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
11342: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
11343: /* printf("Decoderesult Quantitative or Dummy (not with age) nres=%d k1=%d precov[nres=%d][k1=%d]=%.f V%d(=%.f) * V%d(=%.f) \n",nres, k1, nres, k1,precov[nres][k1], Tvardk[k1][1], TinvDoQresult[nres][Tvardk[k1][1]], Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][2]]); */
11344: }else{
11345: k3q= resultmodel[nres][k1]; /* resultmodel[1(V5)] = 25.1=k3q */
11346: k2q=(int)Tvarsel[k3q]; /* Tvarsel[resultmodel[1]]= Tvarsel[1] = 4=k2 */
11347: TinvDoQresult[nres][(int)Tvarsel[k3q]]=Tvalsel[k3q]; /* TinvDoQresult[nres][5]=25.1 */
11348: precov[nres][k1]=Tvalsel[k3q];
11349: }
1.342 brouard 11350: /* printf("Decoderesult Quantitative with age nres=%d, k1=%d, precov[nres=%d][k1=%d]=%f Tvar[%d]=V%d V(k2q=%d)= Tvarsel[%d]=%d, Tvalsel[%d]=%f\n",nres, k1, nres, k1,precov[nres][k1], k1, Tvar[k1], k2q, k3q, Tvarsel[k3q], k3q, Tvalsel[k3q]); */
1.349 brouard 11351: }else if(Typevar[k1]==2 || Typevar[k1]==3 ){ /* For product quant or dummy (with or without age) */
1.332 brouard 11352: precov[nres][k1]=TinvDoQresult[nres][Tvardk[k1][1]] * TinvDoQresult[nres][Tvardk[k1][2]];
1.342 brouard 11353: /* printf("Decoderesult Quantitative or Dummy (not with age) nres=%d k1=%d precov[nres=%d][k1=%d]=%.f V%d(=%.f) * V%d(=%.f) \n",nres, k1, nres, k1,precov[nres][k1], Tvardk[k1][1], TinvDoQresult[nres][Tvardk[k1][1]], Tvardk[k1][2], TinvDoQresult[nres][Tvardk[k1][2]]); */
1.330 brouard 11354: }else{
1.332 brouard 11355: printf("Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
11356: fprintf(ficlog,"Error Decoderesult probably a product Dummy[%d]==%d && Typevar[%d]==%d\n", k1, Dummy[k1], k1, Typevar[k1]);
1.235 brouard 11357: }
11358: }
1.234 brouard 11359:
1.334 brouard 11360: TKresult[nres]=++k; /* Number of combinations of dummies for the nresult and the model =Tvalsel[k3]*pow(2,k4) + 1*/
1.230 brouard 11361: return (0);
11362: }
1.235 brouard 11363:
1.230 brouard 11364: int decodemodel( char model[], int lastobs)
11365: /**< This routine decodes the model and returns:
1.224 brouard 11366: * Model V1+V2+V3+V8+V7*V8+V5*V6+V8*age+V3*age+age*age
11367: * - nagesqr = 1 if age*age in the model, otherwise 0.
11368: * - cptcovt total number of covariates of the model nbocc(+)+1 = 8 excepting constant and age and age*age
11369: * - cptcovn or number of covariates k of the models excluding age*products =6 and age*age
11370: * - cptcovage number of covariates with age*products =2
11371: * - cptcovs number of simple covariates
1.339 brouard 11372: * ncovcolt=ncovcol+nqv+ntv+nqtv total of covariates in the data, not in the model equation
1.224 brouard 11373: * - Tvar[k] is the id of the kth covariate Tvar[1]@12 {1, 2, 3, 8, 10, 11, 8, 3, 7, 8, 5, 6}, thus Tvar[5=V7*V8]=10
1.339 brouard 11374: * which is a new column after the 9 (ncovcol+nqv+ntv+nqtv) variables.
1.319 brouard 11375: * - if k is a product Vn*Vm, covar[k][i] is filled with correct values for each individual
1.224 brouard 11376: * - Tprod[l] gives the kth covariates of the product Vn*Vm l=1 to cptcovprod-cptcovage
11377: * Tprod[1]@2 {5, 6}: position of first product V7*V8 is 5, and second V5*V6 is 6.
11378: * - Tvard[k] p Tvard[1][1]@4 {7, 8, 5, 6} for V7*V8 and V5*V6 .
11379: */
1.319 brouard 11380: /* V2+V1+V4+V3*age Tvar[4]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1, Tage[1]=2 */
1.136 brouard 11381: {
1.238 brouard 11382: int i, j, k, ks, v;
1.349 brouard 11383: int n,m;
11384: int j1, k1, k11, k12, k2, k3, k4;
11385: char modelsav[300];
11386: char stra[300], strb[300], strc[300], strd[300],stre[300],strf[300];
1.187 brouard 11387: char *strpt;
1.349 brouard 11388: int **existcomb;
11389:
11390: existcomb=imatrix(1,NCOVMAX,1,NCOVMAX);
11391: for(i=1;i<=NCOVMAX;i++)
11392: for(j=1;j<=NCOVMAX;j++)
11393: existcomb[i][j]=0;
11394:
1.145 brouard 11395: /*removespace(model);*/
1.136 brouard 11396: if (strlen(model) >1){ /* If there is at least 1 covariate */
1.349 brouard 11397: j=0, j1=0, k1=0, k12=0, k2=-1, ks=0, cptcovn=0;
1.137 brouard 11398: if (strstr(model,"AGE") !=0){
1.192 brouard 11399: printf("Error. AGE must be in lower case 'age' model=1+age+%s. ",model);
11400: fprintf(ficlog,"Error. AGE must be in lower case model=1+age+%s. ",model);fflush(ficlog);
1.136 brouard 11401: return 1;
11402: }
1.141 brouard 11403: if (strstr(model,"v") !=0){
1.338 brouard 11404: printf("Error. 'v' must be in upper case 'V' model=1+age+%s ",model);
11405: fprintf(ficlog,"Error. 'v' must be in upper case model=1+age+%s ",model);fflush(ficlog);
1.141 brouard 11406: return 1;
11407: }
1.187 brouard 11408: strcpy(modelsav,model);
11409: if ((strpt=strstr(model,"age*age")) !=0){
1.338 brouard 11410: printf(" strpt=%s, model=1+age+%s\n",strpt, model);
1.187 brouard 11411: if(strpt != model){
1.338 brouard 11412: printf("Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11413: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11414: corresponding column of parameters.\n",model);
1.338 brouard 11415: fprintf(ficlog,"Error in model: 'model=1+age+%s'; 'age*age' should in first place before other covariates\n \
1.192 brouard 11416: 'model=1+age+age*age+V1.' or 'model=1+age+age*age+V1+V1*age.', please swap as well as \n \
1.187 brouard 11417: corresponding column of parameters.\n",model); fflush(ficlog);
1.234 brouard 11418: return 1;
1.225 brouard 11419: }
1.187 brouard 11420: nagesqr=1;
11421: if (strstr(model,"+age*age") !=0)
1.234 brouard 11422: substrchaine(modelsav, model, "+age*age");
1.187 brouard 11423: else if (strstr(model,"age*age+") !=0)
1.234 brouard 11424: substrchaine(modelsav, model, "age*age+");
1.187 brouard 11425: else
1.234 brouard 11426: substrchaine(modelsav, model, "age*age");
1.187 brouard 11427: }else
11428: nagesqr=0;
1.349 brouard 11429: if (strlen(modelsav) >1){ /* V2 +V3 +V4 +V6 +V7 +V6*V2 +V7*V2 +V6*V3 +V7*V3 +V6*V4 +V7*V4 +age*V2 +age*V3 +age*V4 +age*V6 +age*V7 +age*V6*V2 +V7*V2 +age*V6*V3 +age*V7*V3 +age*V6*V4 +age*V7*V4 */
1.187 brouard 11430: j=nbocc(modelsav,'+'); /**< j=Number of '+' */
11431: j1=nbocc(modelsav,'*'); /**< j1=Number of '*' */
1.351 brouard 11432: cptcovs=0; /**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age => V1 + V3 =4+1-3=2 Wrong */
1.187 brouard 11433: cptcovt= j+1; /* Number of total covariates in the model, not including
1.225 brouard 11434: * cst, age and age*age
11435: * V1+V1*age+ V3 + V3*V4+age*age=> 3+1=4*/
11436: /* including age products which are counted in cptcovage.
11437: * but the covariates which are products must be treated
11438: * separately: ncovn=4- 2=2 (V1+V3). */
1.349 brouard 11439: cptcovprod=0; /**< Number of products V1*V2 +v3*age = 2 */
11440: cptcovdageprod=0; /* Number of doouble products with age age*Vn*VM or Vn*age*Vm or Vn*Vm*age */
1.187 brouard 11441: cptcovprodnoage=0; /**< Number of covariate products without age: V3*V4 =1 */
1.349 brouard 11442: cptcovprodage=0;
11443: /* cptcovprodage=nboccstr(modelsav,"age");*/
1.225 brouard 11444:
1.187 brouard 11445: /* Design
11446: * V1 V2 V3 V4 V5 V6 V7 V8 V9 Weight
11447: * < ncovcol=8 >
11448: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8
11449: * k= 1 2 3 4 5 6 7 8
11450: * cptcovn number of covariates (not including constant and age ) = # of + plus 1 = 7+1=8
1.345 brouard 11451: * covar[k,i], are for fixed covariates, value of kth covariate if not including age for individual i:
1.224 brouard 11452: * covar[1][i]= (V1), covar[4][i]=(V4), covar[8][i]=(V8)
11453: * Tvar[k] # of the kth covariate: Tvar[1]=2 Tvar[2]=1 Tvar[4]=3 Tvar[8]=8
1.187 brouard 11454: * if multiplied by age: V3*age Tvar[3=V3*age]=3 (V3) Tvar[7]=8 and
11455: * Tage[++cptcovage]=k
1.345 brouard 11456: * if products, new covar are created after ncovcol + nqv (quanti fixed) with k1
1.187 brouard 11457: * Tvar[k]=ncovcol+k1; # of the kth covariate product: Tvar[5]=ncovcol+1=10 Tvar[6]=ncovcol+1=11
11458: * Tprod[k1]=k; Tprod[1]=5 Tprod[2]= 6; gives the position of the k1th product
11459: * Tvard[k1][1]=m Tvard[k1][2]=m; Tvard[1][1]=5 (V5) Tvard[1][2]=6 Tvard[2][1]=7 (V7) Tvard[2][2]=8
11460: * Tvar[cptcovn+k2]=Tvard[k1][1];Tvar[cptcovn+k2+1]=Tvard[k1][2];
11461: * Tvar[8+1]=5;Tvar[8+2]=6;Tvar[8+3]=7;Tvar[8+4]=8 inverted
11462: * V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11
1.345 brouard 11463: * < ncovcol=8 8 fixed covariate. Additional starts at 9 (V5*V6) and 10(V7*V8) >
1.187 brouard 11464: * Model V2 + V1 + V3*age + V3 + V5*V6 + V7*V8 + V8*age + V8 d1 d1 d2 d2
11465: * k= 1 2 3 4 5 6 7 8 9 10 11 12
1.345 brouard 11466: * Tvard[k]= 2 1 3 3 10 11 8 8 5 6 7 8
11467: * p Tvar[1]@12={2, 1, 3, 3, 9, 10, 8, 8}
1.187 brouard 11468: * p Tprod[1]@2={ 6, 5}
11469: *p Tvard[1][1]@4= {7, 8, 5, 6}
11470: * covar[k][i]= V2 V1 ? V3 V5*V6? V7*V8? ? V8
11471: * cov[Tage[kk]+2]=covar[Tvar[Tage[kk]]][i]*cov[2];
1.319 brouard 11472: *How to reorganize? Tvars(orted)
1.187 brouard 11473: * Model V1 + V2 + V3 + V8 + V5*V6 + V7*V8 + V3*age + V8*age
11474: * Tvars {2, 1, 3, 3, 11, 10, 8, 8, 7, 8, 5, 6}
11475: * {2, 1, 4, 8, 5, 6, 3, 7}
11476: * Struct []
11477: */
1.225 brouard 11478:
1.187 brouard 11479: /* This loop fills the array Tvar from the string 'model'.*/
11480: /* j is the number of + signs in the model V1+V2+V3 j=2 i=3 to 1 */
11481: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4 */
11482: /* k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tage[cptcovage=1]=4 */
11483: /* k=3 V4 Tvar[k=3]= 4 (from V4) */
11484: /* k=2 V1 Tvar[k=2]= 1 (from V1) */
11485: /* k=1 Tvar[1]=2 (from V2) */
11486: /* k=5 Tvar[5] */
11487: /* for (k=1; k<=cptcovn;k++) { */
1.198 brouard 11488: /* cov[2+k]=nbcode[Tvar[k]][codtabm(ij,Tvar[k])]; */
1.187 brouard 11489: /* } */
1.198 brouard 11490: /* for (k=1; k<=cptcovage;k++) cov[2+Tage[k]]=nbcode[Tvar[Tage[k]]][codtabm(ij,Tvar[Tage[k])]]*cov[2]; */
1.187 brouard 11491: /*
11492: * Treating invertedly V2+V1+V3*age+V2*V4 is as if written V2*V4 +V3*age + V1 + V2 */
1.227 brouard 11493: for(k=cptcovt; k>=1;k--){ /**< Number of covariates not including constant and age, neither age*age*/
11494: Tvar[k]=0; Tprod[k]=0; Tposprod[k]=0;
11495: }
1.187 brouard 11496: cptcovage=0;
1.351 brouard 11497:
11498: /* First loop in order to calculate */
11499: /* for age*VN*Vm
11500: * Provides, Typevar[k], Tage[cptcovage], existcomb[n][m], FixedV[ncovcolt+k12]
11501: * Tprod[k1]=k Tposprod[k]=k1; Tvard[k1][1] =m;
11502: */
11503: /* Needs FixedV[Tvardk[k][1]] */
11504: /* For others:
11505: * Sets Typevar[k];
11506: * Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
11507: * Tposprod[k]=k11;
11508: * Tprod[k11]=k;
11509: * Tvardk[k][1] =m;
11510: * Needs FixedV[Tvardk[k][1]] == 0
11511: */
11512:
1.319 brouard 11513: for(k=1; k<=cptcovt;k++){ /* Loop on total covariates of the model line */
11514: cutl(stra,strb,modelsav,'+'); /* keeps in strb after the first '+' cutl from left to right
11515: modelsav==V2+V1+V5*age+V4+V3*age strb=V3*age stra=V2+V1V5*age+V4 */ /* <model> "V5+V4+V3+V4*V3+V5*age+V1*age+V1" strb="V5" stra="V4+V3+V4*V3+V5*age+V1*age+V1" */
11516: if (nbocc(modelsav,'+')==0)
11517: strcpy(strb,modelsav); /* and analyzes it */
1.234 brouard 11518: /* printf("i=%d a=%s b=%s sav=%s\n",i, stra,strb,modelsav);*/
11519: /*scanf("%d",i);*/
1.349 brouard 11520: if (strchr(strb,'*')) { /**< Model includes a product V2+V1+V5*age+ V4+V3*age strb=V3*age OR double product with age strb=age*V6*V2 or V6*V2*age or V6*age*V2 */
11521: cutl(strc,strd,strb,'*'); /**< k=1 strd*strc Vm*Vn: strb=V3*age(input) strc=age strd=V3 ; V3*V2 strc=V2, strd=V3 OR strb=age*V6*V2 strc=V6*V2 strd=age OR c=V2*age OR c=age*V2 */
11522: if(strchr(strc,'*')) { /**< Model with age and DOUBLE product: allowed since 0.99r44, strc=V6*V2 or V2*age or age*V2, strd=age or V6 or V6 */
11523: Typevar[k]=3; /* 3 for age and double product age*Vn*Vm varying of fixed */
11524: if(strstr(strc,"age")!=0) { /* It means that strc=V2*age or age*V2 and thus that strd=Vn */
11525: cutl(stre,strf,strc,'*') ; /* strf=age or Vm, stre=Vm or age. If strc=V6*V2 then strf=V6 and stre=V2 */
11526: strcpy(strc,strb); /* save strb(=age*Vn*Vm) into strc */
11527: /* We want strb=Vn*Vm */
11528: if(strcmp(strf,"age")==0){ /* strf is "age" so that stre=Vm =V2 . */
11529: strcpy(strb,strd);
11530: strcat(strb,"*");
11531: strcat(strb,stre);
11532: }else{ /* strf=Vm If strf=V6 then stre=V2 */
11533: strcpy(strb,strf);
11534: strcat(strb,"*");
11535: strcat(strb,stre);
11536: strcpy(strd,strb); /* in order for strd to not be "age" for next test (will be Vn*Vm */
11537: }
1.351 brouard 11538: /* printf("DEBUG FIXED k=%d, Tage[k]=%d, Tvar[Tage[k]=%d,FixedV[Tvar[Tage[k]]]=%d\n",k,Tage[k],Tvar[Tage[k]],FixedV[Tvar[Tage[k]]]); */
11539: /* FixedV[Tvar[Tage[k]]]=0; /\* HERY not sure if V7*V4*age Fixed might not exist yet*\/ */
1.349 brouard 11540: }else{ /* strc=Vn*Vm (and strd=age) and should be strb=Vn*Vm but want to keep original strb double product */
11541: strcpy(stre,strb); /* save full b in stre */
11542: strcpy(strb,strc); /* save short c in new short b for next block strb=Vn*Vm*/
11543: strcpy(strf,strc); /* save short c in new short f */
11544: cutl(strc,strd,strf,'*'); /* We get strd=Vn and strc=Vm for next block (strb=Vn*Vm)*/
11545: /* strcpy(strc,stre);*/ /* save full e in c for future */
11546: }
11547: cptcovdageprod++; /* double product with age Which product is it? */
11548: /* strcpy(strb,strc); /\* strb was age*V6*V2 or V6*V2*age or V6*age*V2 IS now V6*V2 or V2*age or age*V2 *\/ */
11549: /* cutl(strc,strd,strb,'*'); /\* strd= V6 or V2 or age and strc= V2 or age or V2 *\/ */
1.234 brouard 11550: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
1.349 brouard 11551: n=atoi(stre);
1.234 brouard 11552: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
1.349 brouard 11553: m=atoi(strc);
11554: cptcovage++; /* Counts the number of covariates which include age as a product */
11555: Tage[cptcovage]=k; /* For age*V3*V2 gives the position in model of covariates associated with age Tage[1]=6 HERY too*/
11556: if(existcomb[n][m] == 0){
11557: /* r /home/brouard/Documents/Recherches/REVES/Zachary/Zach-2022/Feinuo_Sun/Feinuo-threeway/femV12V15_3wayintNBe.imach */
11558: printf("Warning in model combination V%d*V%d should exist in the model before adding V%d*V%d*age !\n",n,m,n,m);
11559: fprintf(ficlog,"Warning in model combination V%d*V%d should exist in the model before adding V%d*V%d*age !\n",n,m,n,m);
11560: fflush(ficlog);
11561: k1++; /* The combination Vn*Vm will be in the model so we create it at k1 */
11562: k12++;
11563: existcomb[n][m]=k1;
11564: existcomb[m][n]=k1;
11565: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1;
11566: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2+ age*V6*V3 Gives the k position of the k1 double product Vn*Vm or age*Vn*Vm*/
11567: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 Gives the k1 double product Vn*Vm or age*Vn*Vm at the k position */
11568: Tvard[k1][1] =m; /* m 1 for V1*/
11569: Tvardk[k][1] =m; /* m 1 for V1*/
11570: Tvard[k1][2] =n; /* n 4 for V4*/
11571: Tvardk[k][2] =n; /* n 4 for V4*/
1.351 brouard 11572: /* Tvar[Tage[cptcovage]]=k1;*/ /* Tvar[6=age*V3*V2]=9 (new fixed covariate) */ /* We don't know about Fixed yet HERE */
1.349 brouard 11573: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* If the product is a fixed covariate then we feed the new column with Vn*Vm */
11574: for (i=1; i<=lastobs;i++){/* For fixed product */
11575: /* Computes the new covariate which is a product of
11576: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11577: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11578: }
11579: cptcovprodage++; /* Counting the number of fixed covariate with age */
11580: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11581: k12++;
11582: FixedV[ncovcolt+k12]=0;
11583: }else{ /*End of FixedV */
11584: cptcovprodvage++; /* Counting the number of varying covariate with age */
11585: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11586: k12++;
11587: FixedV[ncovcolt+k12]=1;
11588: }
11589: }else{ /* k1 Vn*Vm already exists */
11590: k11=existcomb[n][m];
11591: Tposprod[k]=k11; /* OK */
11592: Tvar[k]=Tvar[Tprod[k11]]; /* HERY */
11593: Tvardk[k][1]=m;
11594: Tvardk[k][2]=n;
11595: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* If the product is a fixed covariate then we feed the new column with Vn*Vm */
11596: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11597: cptcovprodage++; /* Counting the number of fixed covariate with age */
11598: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11599: Tvar[Tage[cptcovage]]=k1;
11600: FixedV[ncovcolt+k12]=0; /* We expand Vn*Vm */
11601: k12++;
11602: FixedV[ncovcolt+k12]=0;
11603: }else{ /* Already exists but time varying (and age) */
11604: /*cptcovage++;*/ /* Counts the number of covariates which include age as a product */
11605: /*Tage[cptcovage]=k;*/ /* For age*V3*V2 Tage[1]=V3*V3=9 HERY too*/
11606: /* Tvar[Tage[cptcovage]]=k1; */
11607: cptcovprodvage++;
11608: FixedV[ncovcolt+k12]=1; /* We expand Vn*Vm */
11609: k12++;
11610: FixedV[ncovcolt+k12]=1;
11611: }
11612: }
11613: /* Tage[cptcovage]=k; /\* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 *\/ */
11614: /* Tvar[k]=k11; /\* HERY *\/ */
11615: } else {/* simple product strb=age*Vn so that c=Vn and d=age, or strb=Vn*age so that c=age and d=Vn, or b=Vn*Vm so that c=Vm and d=Vn */
11616: cptcovprod++;
11617: if (strcmp(strc,"age")==0) { /**< Model includes age: strb= Vn*age c=age d=Vn*/
11618: /* covar is not filled and then is empty */
11619: cutl(stre,strb,strd,'V'); /* strd=V3(input): stre="3" */
11620: Tvar[k]=atoi(stre); /* V2+V1+V5*age+V4+V3*age Tvar[5]=3 ; V1+V2*age Tvar[2]=2; V1+V1*age Tvar[2]=1 */
11621: Typevar[k]=1; /* 1 for age product */
11622: cptcovage++; /* Counts the number of covariates which include age as a product */
11623: Tage[cptcovage]=k; /* V2+V1+V4+V3*age Tvar[4]=3, Tage[1] = 4 or V1+V1*age Tvar[2]=1, Tage[1]=2 */
11624: if( FixedV[Tvar[k]] == 0){
11625: cptcovprodage++; /* Counting the number of fixed covariate with age */
11626: }else{
11627: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
11628: }
11629: /*printf("stre=%s ", stre);*/
11630: } else if (strcmp(strd,"age")==0) { /* strb= age*Vn c=Vn */
11631: cutl(stre,strb,strc,'V');
11632: Tvar[k]=atoi(stre);
11633: Typevar[k]=1; /* 1 for age product */
11634: cptcovage++;
11635: Tage[cptcovage]=k;
11636: if( FixedV[Tvar[k]] == 0){
11637: cptcovprodage++; /* Counting the number of fixed covariate with age */
11638: }else{
11639: cptcovprodvage++; /* Counting the number of fixedvarying covariate with age */
1.339 brouard 11640: }
1.349 brouard 11641: }else{ /* for product Vn*Vm */
11642: Typevar[k]=2; /* 2 for product Vn*Vm */
11643: cutl(stre,strb,strc,'V'); /* strc= Vn, stre is n; strb=V3*V2 stre=3 strc=*/
11644: n=atoi(stre);
11645: cutl(strc,strb,strd,'V'); /* strd was Vm, strc is m */
11646: m=atoi(strc);
11647: k1++;
11648: cptcovprodnoage++;
11649: if(existcomb[n][m] != 0 || existcomb[m][n] != 0){
11650: printf("Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
11651: fprintf(ficlog,"Warning in model combination V%d*V%d already exists in the model in position k1=%d!\n",n,m,existcomb[n][m]);
11652: fflush(ficlog);
11653: k11=existcomb[n][m];
11654: Tvar[k]=ncovcol+nqv+ntv+nqtv+k11;
11655: Tposprod[k]=k11;
11656: Tprod[k11]=k;
11657: Tvardk[k][1] =m; /* m 1 for V1*/
11658: /* Tvard[k11][1] =m; /\* n 4 for V4*\/ */
11659: Tvardk[k][2] =n; /* n 4 for V4*/
11660: /* Tvard[k11][2] =n; /\* n 4 for V4*\/ */
11661: }else{ /* combination Vn*Vm doesn't exist we create it (no age)*/
11662: existcomb[n][m]=k1;
11663: existcomb[m][n]=k1;
11664: Tvar[k]=ncovcol+nqv+ntv+nqtv+k1; /* ncovcolt+k1; For model-covariate k tells which data-covariate to use but
11665: because this model-covariate is a construction we invent a new column
11666: which is after existing variables ncovcol+nqv+ntv+nqtv + k1
11667: If already ncovcol=4 and model= V2 + V1 + V1*V4 + age*V3 + V3*V2
11668: thus after V4 we invent V5 and V6 because age*V3 will be computed in 4
11669: Tvar[3=V1*V4]=4+1=5 Tvar[5=V3*V2]=4 + 2= 6, Tvar[4=age*V3]=3 etc */
11670: /* Please remark that the new variables are model dependent */
11671: /* If we have 4 variable but the model uses only 3, like in
11672: * model= V1 + age*V1 + V2 + V3 + age*V2 + age*V3 + V1*V2 + V1*V3
11673: * k= 1 2 3 4 5 6 7 8
11674: * Tvar[k]=1 1 2 3 2 3 (5 6) (and not 4 5 because of V4 missing)
11675: * Tage[kk] [1]= 2 [2]=5 [3]=6 kk=1 to cptcovage=3
11676: * Tvar[Tage[kk]][1]=2 [2]=2 [3]=3
11677: */
11678: /* We need to feed some variables like TvarVV, but later on next loop because of ncovv (k2) is not correct */
11679: Tprod[k1]=k; /* Tprod[1]=3(=V1*V4) for V2+V1+V1*V4+age*V3+V3*V2 +V6*V2*age */
11680: Tposprod[k]=k1; /* Tposprod[3]=1, Tposprod[2]=5 */
11681: Tvard[k1][1] =m; /* m 1 for V1*/
11682: Tvardk[k][1] =m; /* m 1 for V1*/
11683: Tvard[k1][2] =n; /* n 4 for V4*/
11684: Tvardk[k][2] =n; /* n 4 for V4*/
11685: k2=k2+2; /* k2 is initialize to -1, We want to store the n and m in Vn*Vm at the end of Tvar */
11686: /* Tvar[cptcovt+k2]=Tvard[k1][1]; /\* Tvar[(cptcovt=4+k2=1)=5]= 1 (V1) *\/ */
11687: /* Tvar[cptcovt+k2+1]=Tvard[k1][2]; /\* Tvar[(cptcovt=4+(k2=1)+1)=6]= 4 (V4) *\/ */
11688: /*ncovcol=4 and model=V2+V1+V1*V4+age*V3+V3*V2, Tvar[3]=5, Tvar[4]=6, cptcovt=5 */
11689: /* 1 2 3 4 5 | Tvar[5+1)=1, Tvar[7]=2 */
11690: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* If the product is a fixed covariate then we feed the new column with Vn*Vm */
11691: for (i=1; i<=lastobs;i++){/* For fixed product */
11692: /* Computes the new covariate which is a product of
11693: covar[n][i]* covar[m][i] and stores it at ncovol+k1 May not be defined */
11694: covar[ncovcolt+k1][i]=covar[atoi(stre)][i]*covar[atoi(strc)][i];
11695: }
11696: /* TvarVV[k2]=n; */
11697: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11698: /* TvarVV[k2+1]=m; */
11699: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11700: }else{ /* not FixedV */
11701: /* TvarVV[k2]=n; */
11702: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11703: /* TvarVV[k2+1]=m; */
11704: /* FixedV[ncovcolt+k2]=0; /\* or FixedV[Tvar[k]]=0; FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11705: }
11706: } /* End of creation of Vn*Vm if not created by age*Vn*Vm earlier */
11707: } /* End of product Vn*Vm */
11708: } /* End of age*double product or simple product */
11709: }else { /* not a product */
1.234 brouard 11710: /*printf("d=%s c=%s b=%s\n", strd,strc,strb);*/
11711: /* scanf("%d",i);*/
11712: cutl(strd,strc,strb,'V');
11713: ks++; /**< Number of simple covariates dummy or quantitative, fixe or varying */
11714: cptcovn++; /** V4+V3+V5: V4 and V3 timevarying dummy covariates, V5 timevarying quantitative */
11715: Tvar[k]=atoi(strd);
11716: Typevar[k]=0; /* 0 for simple covariates */
11717: }
11718: strcpy(modelsav,stra); /* modelsav=V2+V1+V4 stra=V2+V1+V4 */
1.223 brouard 11719: /*printf("a=%s b=%s sav=%s\n", stra,strb,modelsav);
1.225 brouard 11720: scanf("%d",i);*/
1.187 brouard 11721: } /* end of loop + on total covariates */
1.351 brouard 11722:
11723:
1.187 brouard 11724: } /* end if strlen(modelsave == 0) age*age might exist */
11725: } /* end if strlen(model == 0) */
1.349 brouard 11726: cptcovs=cptcovt - cptcovdageprod - cptcovprod;/**< Number of simple covariates V1 +V1*age +V3 +V3*V4 +age*age + age*v4*V3=> V1 + V3 =4+1-3=2 */
11727:
1.136 brouard 11728: /*The number n of Vn is stored in Tvar. cptcovage =number of age covariate. Tage gives the position of age. cptcovprod= number of products.
11729: If model=V1+V1*age then Tvar[1]=1 Tvar[2]=1 cptcovage=1 Tage[1]=2 cptcovprod=0*/
1.225 brouard 11730:
1.136 brouard 11731: /* printf("tvar1=%d tvar2=%d tvar3=%d cptcovage=%d Tage=%d",Tvar[1],Tvar[2],Tvar[3],cptcovage,Tage[1]);
1.225 brouard 11732: printf("cptcovprod=%d ", cptcovprod);
11733: fprintf(ficlog,"cptcovprod=%d ", cptcovprod);
11734: scanf("%d ",i);*/
11735:
11736:
1.230 brouard 11737: /* Until here, decodemodel knows only the grammar (simple, product, age*) of the model but not what kind
11738: of variable (dummy vs quantitative, fixed vs time varying) is behind. But we know the # of each. */
1.226 brouard 11739: /* ncovcol= 1, nqv=1 | ntv=2, nqtv= 1 = 5 possible variables data: 2 fixed 3, varying
11740: model= V5 + V4 +V3 + V4*V3 + V5*age + V2 + V1*V2 + V1*age + V5*age, V1 is not used saving its place
11741: k = 1 2 3 4 5 6 7 8 9
11742: Tvar[k]= 5 4 3 1+1+2+1+1=6 5 2 7 1 5
1.319 brouard 11743: Typevar[k]= 0 0 0 2 1 0 2 1 0
1.227 brouard 11744: Fixed[k] 1 1 1 1 3 0 0 or 2 2 3
11745: Dummy[k] 1 0 0 0 3 1 1 2 3
11746: Tmodelind[combination of covar]=k;
1.225 brouard 11747: */
11748: /* Dispatching between quantitative and time varying covariates */
1.226 brouard 11749: /* If Tvar[k] >ncovcol it is a product */
1.225 brouard 11750: /* Tvar[k] is the value n of Vn with n varying for 1 to nvcol, or p Vp=Vn*Vm for product */
1.226 brouard 11751: /* Computing effective variables, ie used by the model, that is from the cptcovt variables */
1.318 brouard 11752: printf("Model=1+age+%s\n\
1.349 brouard 11753: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 for double product with age \n\
1.227 brouard 11754: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11755: Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model);
1.318 brouard 11756: fprintf(ficlog,"Model=1+age+%s\n\
1.349 brouard 11757: Typevar: 0 for simple covariate (dummy, quantitative, fixed or varying), 1 for age product, 2 for product, 3 for double product with age \n\
1.227 brouard 11758: Fixed[k] 0=fixed (product or simple), 1 varying, 2 fixed with age product, 3 varying with age product \n\
11759: Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product\n",model);
1.342 brouard 11760: for(k=-1;k<=NCOVMAX; k++){ Fixed[k]=0; Dummy[k]=0;}
11761: for(k=1;k<=NCOVMAX; k++){TvarFind[k]=0; TvarVind[k]=0;}
1.351 brouard 11762:
11763:
11764: /* Second loop for calculating Fixed[k], Dummy[k]*/
11765:
11766:
1.349 brouard 11767: for(k=1, ncovf=0, nsd=0, nsq=0, ncovv=0,ncovva=0,ncovvta=0, ncova=0, ncoveff=0, nqfveff=0, ntveff=0, nqtveff=0, ncovvt=0;k<=cptcovt; k++){ /* or cptocvt loop on k from model */
1.234 brouard 11768: if (Tvar[k] <=ncovcol && Typevar[k]==0 ){ /* Simple fixed dummy (<=ncovcol) covariates */
1.227 brouard 11769: Fixed[k]= 0;
11770: Dummy[k]= 0;
1.225 brouard 11771: ncoveff++;
1.232 brouard 11772: ncovf++;
1.234 brouard 11773: nsd++;
11774: modell[k].maintype= FTYPE;
11775: TvarsD[nsd]=Tvar[k];
11776: TvarsDind[nsd]=k;
1.330 brouard 11777: TnsdVar[Tvar[k]]=nsd;
1.234 brouard 11778: TvarF[ncovf]=Tvar[k];
11779: TvarFind[ncovf]=k;
11780: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11781: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
1.339 brouard 11782: /* }else if( Tvar[k] <=ncovcol && Typevar[k]==2){ /\* Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol *\/ */
1.240 brouard 11783: }else if( Tvar[k] <=ncovcol+nqv && Typevar[k]==0){/* Remind that product Vn*Vm are added in k Only simple fixed quantitative variable */
1.227 brouard 11784: Fixed[k]= 0;
11785: Dummy[k]= 1;
1.230 brouard 11786: nqfveff++;
1.234 brouard 11787: modell[k].maintype= FTYPE;
11788: modell[k].subtype= FQ;
11789: nsq++;
1.334 brouard 11790: TvarsQ[nsq]=Tvar[k]; /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary see below */
11791: TvarsQind[nsq]=k; /* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.232 brouard 11792: ncovf++;
1.234 brouard 11793: TvarF[ncovf]=Tvar[k];
11794: TvarFind[ncovf]=k;
1.231 brouard 11795: TvarFQ[nqfveff]=Tvar[k]-ncovcol; /* TvarFQ[1]=V2-1=1st in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1.230 brouard 11796: TvarFQind[nqfveff]=k; /* TvarFQind[1]=6 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple fixed quantitative variable */
1.242 brouard 11797: }else if( Tvar[k] <=ncovcol+nqv+ntv && Typevar[k]==0){/* Only simple time varying dummy variables */
1.339 brouard 11798: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11799: /* model V1+V3+age*V1+age*V3+V1*V3 */
11800: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11801: ncovvt++;
11802: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11803: TvarVVind[ncovvt]=k; /* TvarVVind[1]=2 (second position in the model equation */
11804:
1.227 brouard 11805: Fixed[k]= 1;
11806: Dummy[k]= 0;
1.225 brouard 11807: ntveff++; /* Only simple time varying dummy variable */
1.234 brouard 11808: modell[k].maintype= VTYPE;
11809: modell[k].subtype= VD;
11810: nsd++;
11811: TvarsD[nsd]=Tvar[k];
11812: TvarsDind[nsd]=k;
1.330 brouard 11813: TnsdVar[Tvar[k]]=nsd; /* To be verified */
1.234 brouard 11814: ncovv++; /* Only simple time varying variables */
11815: TvarV[ncovv]=Tvar[k];
1.242 brouard 11816: TvarVind[ncovv]=k; /* TvarVind[2]=2 TvarVind[3]=3 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Any time varying singele */
1.231 brouard 11817: TvarVD[ntveff]=Tvar[k]; /* TvarVD[1]=V4 TvarVD[2]=V3 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying dummy variable */
11818: TvarVDind[ntveff]=k; /* TvarVDind[1]=2 TvarVDind[2]=3 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying dummy variable */
1.228 brouard 11819: printf("Quasi Tmodelind[%d]=%d,Tvar[Tmodelind[%d]]=V%d, ncovcol=%d, nqv=%d,Tvar[k]- ncovcol-nqv=%d\n",ntveff,k,ntveff,Tvar[k], ncovcol, nqv,Tvar[k]- ncovcol-nqv);
11820: printf("Quasi TmodelInvind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv);
1.231 brouard 11821: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv && Typevar[k]==0){ /* Only simple time varying quantitative variable V5*/
1.339 brouard 11822: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11823: /* model V1+V3+age*V1+age*V3+V1*V3 */
11824: /* Tvar={1, 3, 1, 3, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11825: ncovvt++;
11826: TvarVV[ncovvt]=Tvar[k]; /* TvarVV[1]=V3 (first time varying in the model equation */
11827: TvarVVind[ncovvt]=k; /* TvarVV[1]=V3 (first time varying in the model equation */
11828:
1.234 brouard 11829: Fixed[k]= 1;
11830: Dummy[k]= 1;
11831: nqtveff++;
11832: modell[k].maintype= VTYPE;
11833: modell[k].subtype= VQ;
11834: ncovv++; /* Only simple time varying variables */
11835: nsq++;
1.334 brouard 11836: TvarsQ[nsq]=Tvar[k]; /* k=1 Tvar=5 nsq=1 TvarsQ[1]=5 */ /* Gives the variable name (extended to products) of first nsq simple quantitative covariates (fixed or time vary here) */
11837: TvarsQind[nsq]=k; /* For single quantitative covariate gives the model position of each single quantitative covariate *//* Gives the position in the model equation of the first nsq simple quantitative covariates (fixed or time vary) */
1.234 brouard 11838: TvarV[ncovv]=Tvar[k];
1.242 brouard 11839: TvarVind[ncovv]=k; /* TvarVind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Any time varying singele */
1.231 brouard 11840: TvarVQ[nqtveff]=Tvar[k]; /* TvarVQ[1]=V5 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
11841: TvarVQind[nqtveff]=k; /* TvarVQind[1]=1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */ /* Only simple time varying quantitative variable */
1.234 brouard 11842: TmodelInvQind[nqtveff]=Tvar[k]- ncovcol-nqv-ntv;/* Only simple time varying quantitative variable */
11843: /* Tmodeliqind[k]=nqtveff;/\* Only simple time varying quantitative variable *\/ */
1.349 brouard 11844: /* printf("Quasi TmodelQind[%d]=%d,Tvar[TmodelQind[%d]]=V%d, ncovcol=%d, nqv=%d, ntv=%Ad,Tvar[k]- ncovcol-nqv-ntv=%d\n",nqtveff,k,nqtveff,Tvar[k], ncovcol, nqv, ntv, Tvar[k]- ncovcol-nqv-ntv); */
1.342 brouard 11845: /* printf("Quasi TmodelInvQind[%d]=%d\n",k,Tvar[k]- ncovcol-nqv-ntv); */
1.227 brouard 11846: }else if (Typevar[k] == 1) { /* product with age */
1.234 brouard 11847: ncova++;
11848: TvarA[ncova]=Tvar[k];
11849: TvarAind[ncova]=k;
1.349 brouard 11850: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11851: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
1.231 brouard 11852: if (Tvar[k] <=ncovcol ){ /* Product age with fixed dummy covariatee */
1.240 brouard 11853: Fixed[k]= 2;
11854: Dummy[k]= 2;
11855: modell[k].maintype= ATYPE;
11856: modell[k].subtype= APFD;
1.349 brouard 11857: ncovta++;
11858: TvarAVVA[ncovta]=Tvar[k]; /* (2)age*V3 */
11859: TvarAVVAind[ncovta]=k;
1.240 brouard 11860: /* ncoveff++; */
1.227 brouard 11861: }else if( Tvar[k] <=ncovcol+nqv) { /* Remind that product Vn*Vm are added in k*/
1.240 brouard 11862: Fixed[k]= 2;
11863: Dummy[k]= 3;
11864: modell[k].maintype= ATYPE;
11865: modell[k].subtype= APFQ; /* Product age * fixed quantitative */
1.349 brouard 11866: ncovta++;
11867: TvarAVVA[ncovta]=Tvar[k]; /* */
11868: TvarAVVAind[ncovta]=k;
1.240 brouard 11869: /* nqfveff++; /\* Only simple fixed quantitative variable *\/ */
1.227 brouard 11870: }else if( Tvar[k] <=ncovcol+nqv+ntv ){
1.240 brouard 11871: Fixed[k]= 3;
11872: Dummy[k]= 2;
11873: modell[k].maintype= ATYPE;
11874: modell[k].subtype= APVD; /* Product age * varying dummy */
1.349 brouard 11875: ncovva++;
11876: TvarVVA[ncovva]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11877: TvarVVAind[ncovva]=k;
11878: ncovta++;
11879: TvarAVVA[ncovta]=Tvar[k]; /* */
11880: TvarAVVAind[ncovta]=k;
1.240 brouard 11881: /* ntveff++; /\* Only simple time varying dummy variable *\/ */
1.227 brouard 11882: }else if( Tvar[k] <=ncovcol+nqv+ntv+nqtv){
1.240 brouard 11883: Fixed[k]= 3;
11884: Dummy[k]= 3;
11885: modell[k].maintype= ATYPE;
11886: modell[k].subtype= APVQ; /* Product age * varying quantitative */
1.349 brouard 11887: ncovva++;
11888: TvarVVA[ncovva]=Tvar[k]; /* */
11889: TvarVVAind[ncovva]=k;
11890: ncovta++;
11891: TvarAVVA[ncovta]=Tvar[k]; /* (1)+age*V6 + (2)age*V7 */
11892: TvarAVVAind[ncovta]=k;
1.240 brouard 11893: /* nqtveff++;/\* Only simple time varying quantitative variable *\/ */
1.227 brouard 11894: }
1.349 brouard 11895: }else if( Tposprod[k]>0 && Typevar[k]==2){ /* Detects if fixed product no age Vm*Vn */
11896: printf("MEMORY ERRORR k=%d Tposprod[k]=%d, Typevar[k]=%d\n ",k, Tposprod[k], Typevar[k]);
11897: if(FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){ /* Needs a fixed product Product of fixed dummy (<=ncovcol) covariates For a fixed product k is higher than ncovcol V3*V2 */
11898: printf("MEMORY ERRORR k=%d Tvardk[k][1]=%d, Tvardk[k][2]=%d, FixedV[Tvardk[k][1]]=%d,FixedV[Tvardk[k][2]]=%d\n ",k,Tvardk[k][1],Tvardk[k][2],FixedV[Tvardk[k][1]],FixedV[Tvardk[k][2]]);
11899: Fixed[k]= 0;
11900: Dummy[k]= 0;
11901: ncoveff++;
11902: ncovf++;
11903: /* ncovv++; */
11904: /* TvarVV[ncovv]=Tvardk[k][1]; */
11905: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11906: /* ncovv++; */
11907: /* TvarVV[ncovv]=Tvardk[k][2]; */
11908: /* FixedV[ncovcolt+ncovv]=0; /\* or FixedV[TvarVV[ncovv]]=0 HERE *\/ */
11909: modell[k].maintype= FTYPE;
11910: TvarF[ncovf]=Tvar[k];
11911: /* TnsdVar[Tvar[k]]=nsd; */ /* To be done */
11912: TvarFind[ncovf]=k;
11913: TvarFD[ncoveff]=Tvar[k]; /* TvarFD[1]=V1 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11914: TvarFDind[ncoveff]=k; /* TvarFDind[1]=9 in V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 */
11915: }else{/* product varying Vn * Vm without age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */
11916: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
11917: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
11918: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
11919: k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1, 1} k1=1 first product but second time varying because of V3 */
11920: ncovvt++;
11921: TvarVV[ncovvt]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
11922: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11923: ncovvt++;
11924: TvarVV[ncovvt]=Tvard[k1][2]; /* TvarVV[3]=V3 */
11925: TvarVVind[ncovvt]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
11926:
11927: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
11928: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
11929:
11930: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
11931: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
11932: Fixed[k]= 1;
11933: Dummy[k]= 0;
11934: modell[k].maintype= FTYPE;
11935: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
11936: ncovf++; /* Fixed variables without age */
11937: TvarF[ncovf]=Tvar[k];
11938: TvarFind[ncovf]=k;
11939: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
11940: Fixed[k]= 0; /* Fixed product */
11941: Dummy[k]= 1;
11942: modell[k].maintype= FTYPE;
11943: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
11944: ncovf++; /* Varying variables without age */
11945: TvarF[ncovf]=Tvar[k];
11946: TvarFind[ncovf]=k;
11947: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
11948: Fixed[k]= 1;
11949: Dummy[k]= 0;
11950: modell[k].maintype= VTYPE;
11951: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
11952: ncovv++; /* Varying variables without age */
11953: TvarV[ncovv]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
11954: TvarVind[ncovv]=k;/* TvarVind[1]=5 */
11955: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
11956: Fixed[k]= 1;
11957: Dummy[k]= 1;
11958: modell[k].maintype= VTYPE;
11959: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
11960: ncovv++; /* Varying variables without age */
11961: TvarV[ncovv]=Tvar[k];
11962: TvarVind[ncovv]=k;
11963: }
11964: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
11965: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
11966: Fixed[k]= 0; /* Fixed product */
11967: Dummy[k]= 1;
11968: modell[k].maintype= FTYPE;
11969: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
11970: ncovf++; /* Fixed variables without age */
11971: TvarF[ncovf]=Tvar[k];
11972: TvarFind[ncovf]=k;
11973: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
11974: Fixed[k]= 1;
11975: Dummy[k]= 1;
11976: modell[k].maintype= VTYPE;
11977: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
11978: ncovv++; /* Varying variables without age */
11979: TvarV[ncovv]=Tvar[k];
11980: TvarVind[ncovv]=k;
11981: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
11982: Fixed[k]= 1;
11983: Dummy[k]= 1;
11984: modell[k].maintype= VTYPE;
11985: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
11986: ncovv++; /* Varying variables without age */
11987: TvarV[ncovv]=Tvar[k];
11988: TvarVind[ncovv]=k;
11989: ncovv++; /* Varying variables without age */
11990: TvarV[ncovv]=Tvar[k];
11991: TvarVind[ncovv]=k;
11992: }
11993: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
11994: if(Tvard[k1][2] <=ncovcol){
11995: Fixed[k]= 1;
11996: Dummy[k]= 1;
11997: modell[k].maintype= VTYPE;
11998: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
11999: ncovv++; /* Varying variables without age */
12000: TvarV[ncovv]=Tvar[k];
12001: TvarVind[ncovv]=k;
12002: }else if(Tvard[k1][2] <=ncovcol+nqv){
12003: Fixed[k]= 1;
12004: Dummy[k]= 1;
12005: modell[k].maintype= VTYPE;
12006: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
12007: ncovv++; /* Varying variables without age */
12008: TvarV[ncovv]=Tvar[k];
12009: TvarVind[ncovv]=k;
12010: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
12011: Fixed[k]= 1;
12012: Dummy[k]= 0;
12013: modell[k].maintype= VTYPE;
12014: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
12015: ncovv++; /* Varying variables without age */
12016: TvarV[ncovv]=Tvar[k];
12017: TvarVind[ncovv]=k;
12018: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
12019: Fixed[k]= 1;
12020: Dummy[k]= 1;
12021: modell[k].maintype= VTYPE;
12022: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
12023: ncovv++; /* Varying variables without age */
12024: TvarV[ncovv]=Tvar[k];
12025: TvarVind[ncovv]=k;
12026: }
12027: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
12028: if(Tvard[k1][2] <=ncovcol){
12029: Fixed[k]= 1;
12030: Dummy[k]= 1;
12031: modell[k].maintype= VTYPE;
12032: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
12033: ncovv++; /* Varying variables without age */
12034: TvarV[ncovv]=Tvar[k];
12035: TvarVind[ncovv]=k;
12036: }else if(Tvard[k1][2] <=ncovcol+nqv){
12037: Fixed[k]= 1;
12038: Dummy[k]= 1;
12039: modell[k].maintype= VTYPE;
12040: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
12041: ncovv++; /* Varying variables without age */
12042: TvarV[ncovv]=Tvar[k];
12043: TvarVind[ncovv]=k;
12044: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
12045: Fixed[k]= 1;
12046: Dummy[k]= 1;
12047: modell[k].maintype= VTYPE;
12048: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
12049: ncovv++; /* Varying variables without age */
12050: TvarV[ncovv]=Tvar[k];
12051: TvarVind[ncovv]=k;
12052: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
12053: Fixed[k]= 1;
12054: Dummy[k]= 1;
12055: modell[k].maintype= VTYPE;
12056: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
12057: ncovv++; /* Varying variables without age */
12058: TvarV[ncovv]=Tvar[k];
12059: TvarVind[ncovv]=k;
12060: }
12061: }else{
12062: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12063: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12064: } /*end k1*/
12065: }
12066: }else if(Typevar[k] == 3){ /* product Vn * Vm with age, V1+V3+age*V1+age*V3+V1*V3 looking at V1*V3, Typevar={0, 0, 1, 1, 2}, k=5, V1 is fixed, V3 is timevary, V5 is a product */
1.339 brouard 12067: /*# ID V1 V2 weight birth death 1st s1 V3 V4 V5 2nd s2 */
1.349 brouard 12068: /* model V1+V3+age*V1+age*V3+V1*V3 + V1*V3*age*/
12069: /* Tvar={1, 3, 1, 3, 6, 6}, the 6 comes from the fact that there are already V1, V2, V3, V4, V5 native covariates */
12070: k1=Tposprod[k]; /* Position in the products of product k, Tposprod={0, 0, 0, 0, 1, 1} k1=1 first product but second time varying because of V3 */
12071: ncova++;
12072: TvarA[ncova]=Tvard[k1][1]; /* TvarVV[2]=V1 (because TvarVV[1] was V3, first time varying covariates */
12073: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
12074: ncova++;
12075: TvarA[ncova]=Tvard[k1][2]; /* TvarVV[3]=V3 */
12076: TvarAind[ncova]=k; /* TvarVVind[2]=5 (because TvarVVind[2] was V1*V3 at position 5 */
1.339 brouard 12077:
1.349 brouard 12078: /** Fixed[k] 0=fixed, 1 varying, 2 fixed with age product, 3 varying with age product */
12079: /** Dummy[k] 0=dummy (0 1), 1 quantitative (single or product without age), 2 dummy with age product, 3 quant with age product */
12080: if( FixedV[Tvardk[k][1]] == 0 && FixedV[Tvardk[k][2]] == 0){
12081: ncovta++;
12082: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12083: TvarAVVAind[ncovta]=k;
12084: ncovta++;
12085: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12086: TvarAVVAind[ncovta]=k;
12087: }else{
12088: ncovva++; /* HERY reached */
12089: TvarVVA[ncovva]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12090: TvarVVAind[ncovva]=k;
12091: ncovva++;
12092: TvarVVA[ncovva]=Tvard[k1][2]; /* */
12093: TvarVVAind[ncovva]=k;
12094: ncovta++;
12095: TvarAVVA[ncovta]=Tvard[k1][1]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12096: TvarAVVAind[ncovta]=k;
12097: ncovta++;
12098: TvarAVVA[ncovta]=Tvard[k1][2]; /* age*V6*V3 +age*V7*V3 + age*V6*V4 +age*V7*V4 */
12099: TvarAVVAind[ncovta]=k;
12100: }
1.339 brouard 12101: if(Tvard[k1][1] <=ncovcol){ /* Vn is dummy fixed, (Tvard[1][1]=V1), (Tvard[1][1]=V3 time varying) */
12102: if(Tvard[k1][2] <=ncovcol){ /* Vm is dummy fixed */
1.349 brouard 12103: Fixed[k]= 2;
12104: Dummy[k]= 2;
1.240 brouard 12105: modell[k].maintype= FTYPE;
12106: modell[k].subtype= FPDD; /* Product fixed dummy * fixed dummy */
1.349 brouard 12107: /* TvarF[ncova]=Tvar[k]; /\* Problem to solve *\/ */
12108: /* TvarFind[ncova]=k; */
1.339 brouard 12109: }else if(Tvard[k1][2] <=ncovcol+nqv){ /* Vm is quanti fixed */
1.349 brouard 12110: Fixed[k]= 2; /* Fixed product */
12111: Dummy[k]= 3;
1.240 brouard 12112: modell[k].maintype= FTYPE;
12113: modell[k].subtype= FPDQ; /* Product fixed dummy * fixed quantitative */
1.349 brouard 12114: /* TvarF[ncova]=Tvar[k]; */
12115: /* TvarFind[ncova]=k; */
1.339 brouard 12116: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is a time varying dummy covariate */
1.349 brouard 12117: Fixed[k]= 3;
12118: Dummy[k]= 2;
1.240 brouard 12119: modell[k].maintype= VTYPE;
12120: modell[k].subtype= VPDD; /* Product fixed dummy * varying dummy */
1.349 brouard 12121: TvarV[ncova]=Tvar[k]; /* TvarV[1]=Tvar[5]=5 because there is a V4 */
12122: TvarVind[ncova]=k;/* TvarVind[1]=5 */
1.339 brouard 12123: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is a time varying quantitative covariate */
1.349 brouard 12124: Fixed[k]= 3;
12125: Dummy[k]= 3;
1.240 brouard 12126: modell[k].maintype= VTYPE;
12127: modell[k].subtype= VPDQ; /* Product fixed dummy * varying quantitative */
1.349 brouard 12128: /* ncovv++; /\* Varying variables without age *\/ */
12129: /* TvarV[ncovv]=Tvar[k]; */
12130: /* TvarVind[ncovv]=k; */
1.240 brouard 12131: }
1.339 brouard 12132: }else if(Tvard[k1][1] <=ncovcol+nqv){ /* Vn is fixed quanti */
12133: if(Tvard[k1][2] <=ncovcol){ /* Vm is fixed dummy */
1.349 brouard 12134: Fixed[k]= 2; /* Fixed product */
12135: Dummy[k]= 2;
1.240 brouard 12136: modell[k].maintype= FTYPE;
12137: modell[k].subtype= FPDQ; /* Product fixed quantitative * fixed dummy */
1.349 brouard 12138: /* ncova++; /\* Fixed variables with age *\/ */
12139: /* TvarF[ncovf]=Tvar[k]; */
12140: /* TvarFind[ncovf]=k; */
1.339 brouard 12141: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){ /* Vm is time varying */
1.349 brouard 12142: Fixed[k]= 2;
12143: Dummy[k]= 3;
1.240 brouard 12144: modell[k].maintype= VTYPE;
12145: modell[k].subtype= VPDQ; /* Product fixed quantitative * varying dummy */
1.349 brouard 12146: /* ncova++; /\* Varying variables with age *\/ */
12147: /* TvarV[ncova]=Tvar[k]; */
12148: /* TvarVind[ncova]=k; */
1.339 brouard 12149: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){ /* Vm is time varying quanti */
1.349 brouard 12150: Fixed[k]= 3;
12151: Dummy[k]= 2;
1.240 brouard 12152: modell[k].maintype= VTYPE;
12153: modell[k].subtype= VPQQ; /* Product fixed quantitative * varying quantitative */
1.349 brouard 12154: ncova++; /* Varying variables without age */
12155: TvarV[ncova]=Tvar[k];
12156: TvarVind[ncova]=k;
12157: /* ncova++; /\* Varying variables without age *\/ */
12158: /* TvarV[ncova]=Tvar[k]; */
12159: /* TvarVind[ncova]=k; */
1.240 brouard 12160: }
1.339 brouard 12161: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv){ /* Vn is time varying dummy */
1.240 brouard 12162: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12163: Fixed[k]= 2;
12164: Dummy[k]= 2;
1.240 brouard 12165: modell[k].maintype= VTYPE;
12166: modell[k].subtype= VPDD; /* Product time varying dummy * fixed dummy */
1.349 brouard 12167: /* ncova++; /\* Varying variables with age *\/ */
12168: /* TvarV[ncova]=Tvar[k]; */
12169: /* TvarVind[ncova]=k; */
1.240 brouard 12170: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12171: Fixed[k]= 2;
12172: Dummy[k]= 3;
1.240 brouard 12173: modell[k].maintype= VTYPE;
12174: modell[k].subtype= VPDQ; /* Product time varying dummy * fixed quantitative */
1.349 brouard 12175: /* ncova++; /\* Varying variables with age *\/ */
12176: /* TvarV[ncova]=Tvar[k]; */
12177: /* TvarVind[ncova]=k; */
1.240 brouard 12178: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12179: Fixed[k]= 3;
12180: Dummy[k]= 2;
1.240 brouard 12181: modell[k].maintype= VTYPE;
12182: modell[k].subtype= VPDD; /* Product time varying dummy * time varying dummy */
1.349 brouard 12183: /* ncova++; /\* Varying variables with age *\/ */
12184: /* TvarV[ncova]=Tvar[k]; */
12185: /* TvarVind[ncova]=k; */
1.240 brouard 12186: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12187: Fixed[k]= 3;
12188: Dummy[k]= 3;
1.240 brouard 12189: modell[k].maintype= VTYPE;
12190: modell[k].subtype= VPDQ; /* Product time varying dummy * time varying quantitative */
1.349 brouard 12191: /* ncova++; /\* Varying variables with age *\/ */
12192: /* TvarV[ncova]=Tvar[k]; */
12193: /* TvarVind[ncova]=k; */
1.240 brouard 12194: }
1.339 brouard 12195: }else if(Tvard[k1][1] <=ncovcol+nqv+ntv+nqtv){ /* Vn is time varying quanti */
1.240 brouard 12196: if(Tvard[k1][2] <=ncovcol){
1.349 brouard 12197: Fixed[k]= 2;
12198: Dummy[k]= 2;
1.240 brouard 12199: modell[k].maintype= VTYPE;
12200: modell[k].subtype= VPDQ; /* Product time varying quantitative * fixed dummy */
1.349 brouard 12201: /* ncova++; /\* Varying variables with age *\/ */
12202: /* TvarV[ncova]=Tvar[k]; */
12203: /* TvarVind[ncova]=k; */
1.240 brouard 12204: }else if(Tvard[k1][2] <=ncovcol+nqv){
1.349 brouard 12205: Fixed[k]= 2;
12206: Dummy[k]= 3;
1.240 brouard 12207: modell[k].maintype= VTYPE;
12208: modell[k].subtype= VPQQ; /* Product time varying quantitative * fixed quantitative */
1.349 brouard 12209: /* ncova++; /\* Varying variables with age *\/ */
12210: /* TvarV[ncova]=Tvar[k]; */
12211: /* TvarVind[ncova]=k; */
1.240 brouard 12212: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv){
1.349 brouard 12213: Fixed[k]= 3;
12214: Dummy[k]= 2;
1.240 brouard 12215: modell[k].maintype= VTYPE;
12216: modell[k].subtype= VPDQ; /* Product time varying quantitative * time varying dummy */
1.349 brouard 12217: /* ncova++; /\* Varying variables with age *\/ */
12218: /* TvarV[ncova]=Tvar[k]; */
12219: /* TvarVind[ncova]=k; */
1.240 brouard 12220: }else if(Tvard[k1][2] <=ncovcol+nqv+ntv+nqtv){
1.349 brouard 12221: Fixed[k]= 3;
12222: Dummy[k]= 3;
1.240 brouard 12223: modell[k].maintype= VTYPE;
12224: modell[k].subtype= VPQQ; /* Product time varying quantitative * time varying quantitative */
1.349 brouard 12225: /* ncova++; /\* Varying variables with age *\/ */
12226: /* TvarV[ncova]=Tvar[k]; */
12227: /* TvarVind[ncova]=k; */
1.240 brouard 12228: }
1.227 brouard 12229: }else{
1.240 brouard 12230: printf("Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12231: fprintf(ficlog,"Error unknown type of covariate: Tvard[%d][1]=%d,Tvard[%d][2]=%d\n",k1,Tvard[k1][1],k1,Tvard[k1][2]);
12232: } /*end k1*/
1.349 brouard 12233: } else{
1.226 brouard 12234: printf("Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
12235: fprintf(ficlog,"Error, current version can't treat for performance reasons, Tvar[%d]=%d, Typevar[%d]=%d\n", k, Tvar[k], k, Typevar[k]);
1.225 brouard 12236: }
1.342 brouard 12237: /* printf("Decodemodel, k=%d, Tvar[%d]=V%d,Typevar=%d, Fixed=%d, Dummy=%d\n",k, k,Tvar[k],Typevar[k],Fixed[k],Dummy[k]); */
12238: /* printf(" modell[%d].maintype=%d, modell[%d].subtype=%d\n",k,modell[k].maintype,k,modell[k].subtype); */
1.227 brouard 12239: fprintf(ficlog,"Decodemodel, k=%d, Tvar[%d]=V%d,Typevar=%d, Fixed=%d, Dummy=%d\n",k, k,Tvar[k],Typevar[k],Fixed[k],Dummy[k]);
12240: }
1.349 brouard 12241: ncovvta=ncovva;
1.227 brouard 12242: /* Searching for doublons in the model */
12243: for(k1=1; k1<= cptcovt;k1++){
12244: for(k2=1; k2 <k1;k2++){
1.285 brouard 12245: /* if((Typevar[k1]==Typevar[k2]) && (Fixed[Tvar[k1]]==Fixed[Tvar[k2]]) && (Dummy[Tvar[k1]]==Dummy[Tvar[k2]] )){ */
12246: if((Typevar[k1]==Typevar[k2]) && (Fixed[k1]==Fixed[k2]) && (Dummy[k1]==Dummy[k2] )){
1.234 brouard 12247: if((Typevar[k1] == 0 || Typevar[k1] == 1)){ /* Simple or age product */
12248: if(Tvar[k1]==Tvar[k2]){
1.338 brouard 12249: printf("Error duplication in the model=1+age+%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[k1],Dummy[k1]);
12250: fprintf(ficlog,"Error duplication in the model=1+age+%s at positions (+) %d and %d, Tvar[%d]=V%d, Tvar[%d]=V%d, Typevar=%d, Fixed=%d, Dummy=%d\n", model, k1,k2, k1, Tvar[k1], k2, Tvar[k2],Typevar[k1],Fixed[k1],Dummy[k1]); fflush(ficlog);
1.234 brouard 12251: return(1);
12252: }
12253: }else if (Typevar[k1] ==2){
12254: k3=Tposprod[k1];
12255: k4=Tposprod[k2];
12256: if( ((Tvard[k3][1]== Tvard[k4][1])&&(Tvard[k3][2]== Tvard[k4][2])) || ((Tvard[k3][1]== Tvard[k4][2])&&(Tvard[k3][2]== Tvard[k4][1])) ){
1.338 brouard 12257: printf("Error duplication in the model=1+age+%s at positions (+) %d and %d, V%d*V%d, Typevar=%d, Fixed=%d, Dummy=%d\n",model, k1,k2, Tvard[k3][1], Tvard[k3][2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]);
12258: fprintf(ficlog,"Error duplication in the model=1+age+%s at positions (+) %d and %d, V%d*V%d, Typevar=%d, Fixed=%d, Dummy=%d\n",model, k1,k2, Tvard[k3][1], Tvard[k3][2],Typevar[k1],Fixed[Tvar[k1]],Dummy[Tvar[k1]]); fflush(ficlog);
1.234 brouard 12259: return(1);
12260: }
12261: }
1.227 brouard 12262: }
12263: }
1.225 brouard 12264: }
12265: printf("ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
12266: fprintf(ficlog,"ncoveff=%d, nqfveff=%d, ntveff=%d, nqtveff=%d, cptcovn=%d\n",ncoveff,nqfveff,ntveff,nqtveff,cptcovn);
1.234 brouard 12267: printf("ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd,nsq);
12268: fprintf(ficlog,"ncovf=%d, ncovv=%d, ncova=%d, nsd=%d, nsq=%d\n",ncovf,ncovv,ncova,nsd, nsq);
1.349 brouard 12269:
12270: free_imatrix(existcomb,1,NCOVMAX,1,NCOVMAX);
1.137 brouard 12271: return (0); /* with covar[new additional covariate if product] and Tage if age */
1.164 brouard 12272: /*endread:*/
1.225 brouard 12273: printf("Exiting decodemodel: ");
12274: return (1);
1.136 brouard 12275: }
12276:
1.169 brouard 12277: int calandcheckages(int imx, int maxwav, double *agemin, double *agemax, int *nberr, int *nbwarn )
1.248 brouard 12278: {/* Check ages at death */
1.136 brouard 12279: int i, m;
1.218 brouard 12280: int firstone=0;
12281:
1.136 brouard 12282: for (i=1; i<=imx; i++) {
12283: for(m=2; (m<= maxwav); m++) {
12284: if (((int)mint[m][i]== 99) && (s[m][i] <= nlstate)){
12285: anint[m][i]=9999;
1.216 brouard 12286: if (s[m][i] != -2) /* Keeping initial status of unknown vital status */
12287: s[m][i]=-1;
1.136 brouard 12288: }
12289: if((int)moisdc[i]==99 && (int)andc[i]==9999 && s[m][i]>nlstate){
1.260 brouard 12290: *nberr = *nberr + 1;
1.218 brouard 12291: if(firstone == 0){
12292: firstone=1;
1.260 brouard 12293: printf("Warning (#%d)! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown but status is a death state %d at wave %d. If you don't know the vital status, please enter -2. If he/she is still alive but don't know the state, please code with '-1 or '.'. Here, we do not believe in a death, skipped.\nOther similar cases in log file\n", *nberr,(int)moisdc[i],(int)andc[i],num[i],i,s[m][i],m);
1.218 brouard 12294: }
1.262 brouard 12295: fprintf(ficlog,"Warning (#%d)! Date of death (month %2d and year %4d) of individual %ld on line %d was unknown but status is a death state %d at wave %d. If you don't know the vital status, please enter -2. If he/she is still alive but don't know the state, please code with '-1 or '.'. Here, we do not believe in a death, skipped.\n", *nberr,(int)moisdc[i],(int)andc[i],num[i],i,s[m][i],m);
1.260 brouard 12296: s[m][i]=-1; /* Droping the death status */
1.136 brouard 12297: }
12298: if((int)moisdc[i]==99 && (int)andc[i]!=9999 && s[m][i]>nlstate){
1.169 brouard 12299: (*nberr)++;
1.259 brouard 12300: printf("Error (#%d)! Month of death of individual %ld on line %d was unknown (%2d) (year of death is %4d) and status is a death state %d at wave %d. Please impute an arbitrary (or not) month and rerun. Currently this transition to death will be skipped (status is set to -2).\nOther similar cases in log file\n", *nberr, num[i],i,(int)moisdc[i],(int)andc[i],s[m][i],m);
1.262 brouard 12301: fprintf(ficlog,"Error (#%d)! Month of death of individual %ld on line %d was unknown (%2d) (year of death is %4d) and status is a death state %d at wave %d. Please impute an arbitrary (or not) month and rerun. Currently this transition to death will be skipped (status is set to -2).\n", *nberr, num[i],i,(int)moisdc[i],(int)andc[i],s[m][i],m);
1.259 brouard 12302: s[m][i]=-2; /* We prefer to skip it (and to skip it in version 0.8a1 too */
1.136 brouard 12303: }
12304: }
12305: }
12306:
12307: for (i=1; i<=imx; i++) {
12308: agedc[i]=(moisdc[i]/12.+andc[i])-(moisnais[i]/12.+annais[i]);
12309: for(m=firstpass; (m<= lastpass); m++){
1.214 brouard 12310: if(s[m][i] >0 || s[m][i]==-1 || s[m][i]==-2 || s[m][i]==-4 || s[m][i]==-5){ /* What if s[m][i]=-1 */
1.136 brouard 12311: if (s[m][i] >= nlstate+1) {
1.169 brouard 12312: if(agedc[i]>0){
12313: if((int)moisdc[i]!=99 && (int)andc[i]!=9999){
1.136 brouard 12314: agev[m][i]=agedc[i];
1.214 brouard 12315: /*if(moisdc[i]==99 && andc[i]==9999) s[m][i]=-1;*/
1.169 brouard 12316: }else {
1.136 brouard 12317: if ((int)andc[i]!=9999){
12318: nbwarn++;
12319: printf("Warning negative age at death: %ld line:%d\n",num[i],i);
12320: fprintf(ficlog,"Warning negative age at death: %ld line:%d\n",num[i],i);
12321: agev[m][i]=-1;
12322: }
12323: }
1.169 brouard 12324: } /* agedc > 0 */
1.214 brouard 12325: } /* end if */
1.136 brouard 12326: else if(s[m][i] !=9){ /* Standard case, age in fractional
12327: years but with the precision of a month */
12328: agev[m][i]=(mint[m][i]/12.+1./24.+anint[m][i])-(moisnais[i]/12.+1./24.+annais[i]);
12329: if((int)mint[m][i]==99 || (int)anint[m][i]==9999)
12330: agev[m][i]=1;
12331: else if(agev[m][i] < *agemin){
12332: *agemin=agev[m][i];
12333: printf(" Min anint[%d][%d]=%.2f annais[%d]=%.2f, agemin=%.2f\n",m,i,anint[m][i], i,annais[i], *agemin);
12334: }
12335: else if(agev[m][i] >*agemax){
12336: *agemax=agev[m][i];
1.156 brouard 12337: /* printf(" Max anint[%d][%d]=%.0f annais[%d]=%.0f, agemax=%.2f\n",m,i,anint[m][i], i,annais[i], *agemax);*/
1.136 brouard 12338: }
12339: /*agev[m][i]=anint[m][i]-annais[i];*/
12340: /* agev[m][i] = age[i]+2*m;*/
1.214 brouard 12341: } /* en if 9*/
1.136 brouard 12342: else { /* =9 */
1.214 brouard 12343: /* printf("Debug num[%d]=%ld s[%d][%d]=%d\n",i,num[i], m,i, s[m][i]); */
1.136 brouard 12344: agev[m][i]=1;
12345: s[m][i]=-1;
12346: }
12347: }
1.214 brouard 12348: else if(s[m][i]==0) /*= 0 Unknown */
1.136 brouard 12349: agev[m][i]=1;
1.214 brouard 12350: else{
12351: printf("Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12352: fprintf(ficlog, "Warning, num[%d]=%ld, s[%d][%d]=%d\n", i, num[i], m, i,s[m][i]);
12353: agev[m][i]=0;
12354: }
12355: } /* End for lastpass */
12356: }
1.136 brouard 12357:
12358: for (i=1; i<=imx; i++) {
12359: for(m=firstpass; (m<=lastpass); m++){
12360: if (s[m][i] > (nlstate+ndeath)) {
1.169 brouard 12361: (*nberr)++;
1.136 brouard 12362: printf("Error: on wave %d of individual %d status %d > (nlstate+ndeath)=(%d+%d)=%d\n",m,i,s[m][i],nlstate, ndeath, nlstate+ndeath);
12363: fprintf(ficlog,"Error: on wave %d of individual %d status %d > (nlstate+ndeath)=(%d+%d)=%d\n",m,i,s[m][i],nlstate, ndeath, nlstate+ndeath);
12364: return 1;
12365: }
12366: }
12367: }
12368:
12369: /*for (i=1; i<=imx; i++){
12370: for (m=firstpass; (m<lastpass); m++){
12371: printf("%ld %d %.lf %d %d\n", num[i],(covar[1][i]),agev[m][i],s[m][i],s[m+1][i]);
12372: }
12373:
12374: }*/
12375:
12376:
1.139 brouard 12377: printf("Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
12378: fprintf(ficlog,"Total number of individuals= %d, Agemin = %.2f, Agemax= %.2f\n\n", imx, *agemin, *agemax);
1.136 brouard 12379:
12380: return (0);
1.164 brouard 12381: /* endread:*/
1.136 brouard 12382: printf("Exiting calandcheckages: ");
12383: return (1);
12384: }
12385:
1.172 brouard 12386: #if defined(_MSC_VER)
12387: /*printf("Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12388: /*fprintf(ficlog, "Visual C++ compiler: %s \n;", _MSC_FULL_VER);*/
12389: //#include "stdafx.h"
12390: //#include <stdio.h>
12391: //#include <tchar.h>
12392: //#include <windows.h>
12393: //#include <iostream>
12394: typedef BOOL(WINAPI *LPFN_ISWOW64PROCESS) (HANDLE, PBOOL);
12395:
12396: LPFN_ISWOW64PROCESS fnIsWow64Process;
12397:
12398: BOOL IsWow64()
12399: {
12400: BOOL bIsWow64 = FALSE;
12401:
12402: //typedef BOOL (APIENTRY *LPFN_ISWOW64PROCESS)
12403: // (HANDLE, PBOOL);
12404:
12405: //LPFN_ISWOW64PROCESS fnIsWow64Process;
12406:
12407: HMODULE module = GetModuleHandle(_T("kernel32"));
12408: const char funcName[] = "IsWow64Process";
12409: fnIsWow64Process = (LPFN_ISWOW64PROCESS)
12410: GetProcAddress(module, funcName);
12411:
12412: if (NULL != fnIsWow64Process)
12413: {
12414: if (!fnIsWow64Process(GetCurrentProcess(),
12415: &bIsWow64))
12416: //throw std::exception("Unknown error");
12417: printf("Unknown error\n");
12418: }
12419: return bIsWow64 != FALSE;
12420: }
12421: #endif
1.177 brouard 12422:
1.191 brouard 12423: void syscompilerinfo(int logged)
1.292 brouard 12424: {
12425: #include <stdint.h>
12426:
12427: /* #include "syscompilerinfo.h"*/
1.185 brouard 12428: /* command line Intel compiler 32bit windows, XP compatible:*/
12429: /* /GS /W3 /Gy
12430: /Zc:wchar_t /Zi /O2 /Fd"Release\vc120.pdb" /D "WIN32" /D "NDEBUG" /D
12431: "_CONSOLE" /D "_LIB" /D "_USING_V110_SDK71_" /D "_UNICODE" /D
12432: "UNICODE" /Qipo /Zc:forScope /Gd /Oi /MT /Fa"Release\" /EHsc /nologo
1.186 brouard 12433: /Fo"Release\" /Qprof-dir "Release\" /Fp"Release\IMaCh.pch"
12434: */
12435: /* 64 bits */
1.185 brouard 12436: /*
12437: /GS /W3 /Gy
12438: /Zc:wchar_t /Zi /O2 /Fd"x64\Release\vc120.pdb" /D "WIN32" /D "NDEBUG"
12439: /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo /Zc:forScope
12440: /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Fo"x64\Release\" /Qprof-dir
12441: "x64\Release\" /Fp"x64\Release\IMaCh.pch" */
12442: /* Optimization are useless and O3 is slower than O2 */
12443: /*
12444: /GS /W3 /Gy /Zc:wchar_t /Zi /O3 /Fd"x64\Release\vc120.pdb" /D "WIN32"
12445: /D "NDEBUG" /D "_CONSOLE" /D "_LIB" /D "_UNICODE" /D "UNICODE" /Qipo
12446: /Zc:forScope /Oi /MD /Fa"x64\Release\" /EHsc /nologo /Qparallel
12447: /Fo"x64\Release\" /Qprof-dir "x64\Release\" /Fp"x64\Release\IMaCh.pch"
12448: */
1.186 brouard 12449: /* Link is */ /* /OUT:"visual studio
1.185 brouard 12450: 2013\Projects\IMaCh\Release\IMaCh.exe" /MANIFEST /NXCOMPAT
12451: /PDB:"visual studio
12452: 2013\Projects\IMaCh\Release\IMaCh.pdb" /DYNAMICBASE
12453: "kernel32.lib" "user32.lib" "gdi32.lib" "winspool.lib"
12454: "comdlg32.lib" "advapi32.lib" "shell32.lib" "ole32.lib"
12455: "oleaut32.lib" "uuid.lib" "odbc32.lib" "odbccp32.lib"
12456: /MACHINE:X86 /OPT:REF /SAFESEH /INCREMENTAL:NO
12457: /SUBSYSTEM:CONSOLE",5.01" /MANIFESTUAC:"level='asInvoker'
12458: uiAccess='false'"
12459: /ManifestFile:"Release\IMaCh.exe.intermediate.manifest" /OPT:ICF
12460: /NOLOGO /TLBID:1
12461: */
1.292 brouard 12462:
12463:
1.177 brouard 12464: #if defined __INTEL_COMPILER
1.178 brouard 12465: #if defined(__GNUC__)
12466: struct utsname sysInfo; /* For Intel on Linux and OS/X */
12467: #endif
1.177 brouard 12468: #elif defined(__GNUC__)
1.179 brouard 12469: #ifndef __APPLE__
1.174 brouard 12470: #include <gnu/libc-version.h> /* Only on gnu */
1.179 brouard 12471: #endif
1.177 brouard 12472: struct utsname sysInfo;
1.178 brouard 12473: int cross = CROSS;
12474: if (cross){
12475: printf("Cross-");
1.191 brouard 12476: if(logged) fprintf(ficlog, "Cross-");
1.178 brouard 12477: }
1.174 brouard 12478: #endif
12479:
1.191 brouard 12480: printf("Compiled with:");if(logged)fprintf(ficlog,"Compiled with:");
1.169 brouard 12481: #if defined(__clang__)
1.191 brouard 12482: printf(" Clang/LLVM");if(logged)fprintf(ficlog," Clang/LLVM"); /* Clang/LLVM. ---------------------------------------------- */
1.169 brouard 12483: #endif
12484: #if defined(__ICC) || defined(__INTEL_COMPILER)
1.191 brouard 12485: printf(" Intel ICC/ICPC");if(logged)fprintf(ficlog," Intel ICC/ICPC");/* Intel ICC/ICPC. ------------------------------------------ */
1.169 brouard 12486: #endif
12487: #if defined(__GNUC__) || defined(__GNUG__)
1.191 brouard 12488: printf(" GNU GCC/G++");if(logged)fprintf(ficlog," GNU GCC/G++");/* GNU GCC/G++. --------------------------------------------- */
1.169 brouard 12489: #endif
12490: #if defined(__HP_cc) || defined(__HP_aCC)
1.191 brouard 12491: printf(" Hewlett-Packard C/aC++");if(logged)fprintf(fcilog," Hewlett-Packard C/aC++"); /* Hewlett-Packard C/aC++. ---------------------------------- */
1.169 brouard 12492: #endif
12493: #if defined(__IBMC__) || defined(__IBMCPP__)
1.191 brouard 12494: printf(" IBM XL C/C++"); if(logged) fprintf(ficlog," IBM XL C/C++");/* IBM XL C/C++. -------------------------------------------- */
1.169 brouard 12495: #endif
12496: #if defined(_MSC_VER)
1.191 brouard 12497: printf(" Microsoft Visual Studio");if(logged)fprintf(ficlog," Microsoft Visual Studio");/* Microsoft Visual Studio. --------------------------------- */
1.169 brouard 12498: #endif
12499: #if defined(__PGI)
1.191 brouard 12500: printf(" Portland Group PGCC/PGCPP");if(logged) fprintf(ficlog," Portland Group PGCC/PGCPP");/* Portland Group PGCC/PGCPP. ------------------------------- */
1.169 brouard 12501: #endif
12502: #if defined(__SUNPRO_C) || defined(__SUNPRO_CC)
1.191 brouard 12503: printf(" Oracle Solaris Studio");if(logged)fprintf(ficlog," Oracle Solaris Studio\n");/* Oracle Solaris Studio. ----------------------------------- */
1.167 brouard 12504: #endif
1.191 brouard 12505: printf(" for "); if (logged) fprintf(ficlog, " for ");
1.169 brouard 12506:
1.167 brouard 12507: // http://stackoverflow.com/questions/4605842/how-to-identify-platform-compiler-from-preprocessor-macros
12508: #ifdef _WIN32 // note the underscore: without it, it's not msdn official!
12509: // Windows (x64 and x86)
1.191 brouard 12510: printf("Windows (x64 and x86) ");if(logged) fprintf(ficlog,"Windows (x64 and x86) ");
1.167 brouard 12511: #elif __unix__ // all unices, not all compilers
12512: // Unix
1.191 brouard 12513: printf("Unix ");if(logged) fprintf(ficlog,"Unix ");
1.167 brouard 12514: #elif __linux__
12515: // linux
1.191 brouard 12516: printf("linux ");if(logged) fprintf(ficlog,"linux ");
1.167 brouard 12517: #elif __APPLE__
1.174 brouard 12518: // Mac OS, not sure if this is covered by __posix__ and/or __unix__ though..
1.191 brouard 12519: printf("Mac OS ");if(logged) fprintf(ficlog,"Mac OS ");
1.167 brouard 12520: #endif
12521:
12522: /* __MINGW32__ */
12523: /* __CYGWIN__ */
12524: /* __MINGW64__ */
12525: // http://msdn.microsoft.com/en-us/library/b0084kay.aspx
12526: /* _MSC_VER //the Visual C++ compiler is 17.00.51106.1, the _MSC_VER macro evaluates to 1700. Type cl /? */
12527: /* _MSC_FULL_VER //the Visual C++ compiler is 15.00.20706.01, the _MSC_FULL_VER macro evaluates to 150020706 */
12528: /* _WIN64 // Defined for applications for Win64. */
12529: /* _M_X64 // Defined for compilations that target x64 processors. */
12530: /* _DEBUG // Defined when you compile with /LDd, /MDd, and /MTd. */
1.171 brouard 12531:
1.167 brouard 12532: #if UINTPTR_MAX == 0xffffffff
1.191 brouard 12533: printf(" 32-bit"); if(logged) fprintf(ficlog," 32-bit");/* 32-bit */
1.167 brouard 12534: #elif UINTPTR_MAX == 0xffffffffffffffff
1.191 brouard 12535: printf(" 64-bit"); if(logged) fprintf(ficlog," 64-bit");/* 64-bit */
1.167 brouard 12536: #else
1.191 brouard 12537: printf(" wtf-bit"); if(logged) fprintf(ficlog," wtf-bit");/* wtf */
1.167 brouard 12538: #endif
12539:
1.169 brouard 12540: #if defined(__GNUC__)
12541: # if defined(__GNUC_PATCHLEVEL__)
12542: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12543: + __GNUC_MINOR__ * 100 \
12544: + __GNUC_PATCHLEVEL__)
12545: # else
12546: # define __GNUC_VERSION__ (__GNUC__ * 10000 \
12547: + __GNUC_MINOR__ * 100)
12548: # endif
1.174 brouard 12549: printf(" using GNU C version %d.\n", __GNUC_VERSION__);
1.191 brouard 12550: if(logged) fprintf(ficlog, " using GNU C version %d.\n", __GNUC_VERSION__);
1.176 brouard 12551:
12552: if (uname(&sysInfo) != -1) {
12553: printf("Running on: %s %s %s %s %s\n",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.191 brouard 12554: if(logged) fprintf(ficlog,"Running on: %s %s %s %s %s\n ",sysInfo.sysname, sysInfo.nodename, sysInfo.release, sysInfo.version, sysInfo.machine);
1.176 brouard 12555: }
12556: else
12557: perror("uname() error");
1.179 brouard 12558: //#ifndef __INTEL_COMPILER
12559: #if !defined (__INTEL_COMPILER) && !defined(__APPLE__)
1.174 brouard 12560: printf("GNU libc version: %s\n", gnu_get_libc_version());
1.191 brouard 12561: if(logged) fprintf(ficlog,"GNU libc version: %s\n", gnu_get_libc_version());
1.177 brouard 12562: #endif
1.169 brouard 12563: #endif
1.172 brouard 12564:
1.286 brouard 12565: // void main ()
1.172 brouard 12566: // {
1.169 brouard 12567: #if defined(_MSC_VER)
1.174 brouard 12568: if (IsWow64()){
1.191 brouard 12569: printf("\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
12570: if (logged) fprintf(ficlog, "\nThe program (probably compiled for 32bit) is running under WOW64 (64bit) emulation.\n");
1.174 brouard 12571: }
12572: else{
1.191 brouard 12573: printf("\nThe program is not running under WOW64 (i.e probably on a 64bit Windows).\n");
12574: if (logged) fprintf(ficlog, "\nThe programm is not running under WOW64 (i.e probably on a 64bit Windows).\n");
1.174 brouard 12575: }
1.172 brouard 12576: // printf("\nPress Enter to continue...");
12577: // getchar();
12578: // }
12579:
1.169 brouard 12580: #endif
12581:
1.167 brouard 12582:
1.219 brouard 12583: }
1.136 brouard 12584:
1.219 brouard 12585: int prevalence_limit(double *p, double **prlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp){
1.288 brouard 12586: /*--------------- Prevalence limit (forward period or forward stable prevalence) --------------*/
1.332 brouard 12587: /* Computes the prevalence limit for each combination of the dummy covariates */
1.235 brouard 12588: int i, j, k, i1, k4=0, nres=0 ;
1.202 brouard 12589: /* double ftolpl = 1.e-10; */
1.180 brouard 12590: double age, agebase, agelim;
1.203 brouard 12591: double tot;
1.180 brouard 12592:
1.202 brouard 12593: strcpy(filerespl,"PL_");
12594: strcat(filerespl,fileresu);
12595: if((ficrespl=fopen(filerespl,"w"))==NULL) {
1.288 brouard 12596: printf("Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
12597: fprintf(ficlog,"Problem with forward period (stable) prevalence resultfile: %s\n", filerespl);return 1;
1.202 brouard 12598: }
1.288 brouard 12599: printf("\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
12600: fprintf(ficlog,"\nComputing forward period (stable) prevalence: result on file '%s' \n", filerespl);
1.202 brouard 12601: pstamp(ficrespl);
1.288 brouard 12602: fprintf(ficrespl,"# Forward period (stable) prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.202 brouard 12603: fprintf(ficrespl,"#Age ");
12604: for(i=1; i<=nlstate;i++) fprintf(ficrespl,"%d-%d ",i,i);
12605: fprintf(ficrespl,"\n");
1.180 brouard 12606:
1.219 brouard 12607: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
1.180 brouard 12608:
1.219 brouard 12609: agebase=ageminpar;
12610: agelim=agemaxpar;
1.180 brouard 12611:
1.227 brouard 12612: /* i1=pow(2,ncoveff); */
1.234 brouard 12613: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
1.219 brouard 12614: if (cptcovn < 1){i1=1;}
1.180 brouard 12615:
1.337 brouard 12616: /* for(k=1; k<=i1;k++){ /\* For each combination k of dummy covariates in the model *\/ */
1.238 brouard 12617: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12618: k=TKresult[nres];
1.338 brouard 12619: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12620: /* if(i1 != 1 && TKresult[nres]!= k) /\* We found the combination k corresponding to the resultline value of dummies *\/ */
12621: /* continue; */
1.235 brouard 12622:
1.238 brouard 12623: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12624: /* for(cptcov=1,k=0;cptcov<=1;cptcov++){ */
12625: //for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){
12626: /* k=k+1; */
12627: /* to clean */
1.332 brouard 12628: /*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*/
1.238 brouard 12629: fprintf(ficrespl,"#******");
12630: printf("#******");
12631: fprintf(ficlog,"#******");
1.337 brouard 12632: for(j=1;j<=cptcovs ;j++) {/**< cptcovs number of SIMPLE covariates in the model or resultline V2+V1 =2 (dummy or quantit or time varying) */
1.332 brouard 12633: /* fprintf(ficrespl," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,Tvaraff[j])]); /\* Here problem for varying dummy*\/ */
1.337 brouard 12634: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12635: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12636: fprintf(ficrespl," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12637: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12638: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12639: }
12640: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12641: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12642: /* fprintf(ficrespl," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12643: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12644: /* } */
1.238 brouard 12645: fprintf(ficrespl,"******\n");
12646: printf("******\n");
12647: fprintf(ficlog,"******\n");
12648: if(invalidvarcomb[k]){
12649: printf("\nCombination (%d) ignored because no case \n",k);
12650: fprintf(ficrespl,"#Combination (%d) ignored because no case \n",k);
12651: fprintf(ficlog,"\nCombination (%d) ignored because no case \n",k);
12652: continue;
12653: }
1.219 brouard 12654:
1.238 brouard 12655: fprintf(ficrespl,"#Age ");
1.337 brouard 12656: /* for(j=1;j<=cptcoveff;j++) { */
12657: /* fprintf(ficrespl,"V%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12658: /* } */
12659: for(j=1;j<=cptcovs;j++) { /* New the quanti variable is added */
12660: fprintf(ficrespl,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12661: }
12662: for(i=1; i<=nlstate;i++) fprintf(ficrespl," %d-%d ",i,i);
12663: fprintf(ficrespl,"Total Years_to_converge\n");
1.227 brouard 12664:
1.238 brouard 12665: for (age=agebase; age<=agelim; age++){
12666: /* for (age=agebase; age<=agebase; age++){ */
1.337 brouard 12667: /**< Computes the prevalence limit in each live state at age x and for covariate combination (k and) nres */
12668: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, ncvyearp, k, nres); /* Nicely done */
1.238 brouard 12669: fprintf(ficrespl,"%.0f ",age );
1.337 brouard 12670: /* for(j=1;j<=cptcoveff;j++) */
12671: /* fprintf(ficrespl,"%d %d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12672: for(j=1;j<=cptcovs;j++)
12673: fprintf(ficrespl,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12674: tot=0.;
12675: for(i=1; i<=nlstate;i++){
12676: tot += prlim[i][i];
12677: fprintf(ficrespl," %.5f", prlim[i][i]);
12678: }
12679: fprintf(ficrespl," %.3f %d\n", tot, *ncvyearp);
12680: } /* Age */
12681: /* was end of cptcod */
1.337 brouard 12682: } /* nres */
12683: /* } /\* for each combination *\/ */
1.219 brouard 12684: return 0;
1.180 brouard 12685: }
12686:
1.218 brouard 12687: int back_prevalence_limit(double *p, double **bprlim, double ageminpar, double agemaxpar, double ftolpl, int *ncvyearp, double dateprev1,double dateprev2, int firstpass, int lastpass, int mobilavproj){
1.288 brouard 12688: /*--------------- Back Prevalence limit (backward stable prevalence) --------------*/
1.218 brouard 12689:
12690: /* Computes the back prevalence limit for any combination of covariate values
12691: * at any age between ageminpar and agemaxpar
12692: */
1.235 brouard 12693: int i, j, k, i1, nres=0 ;
1.217 brouard 12694: /* double ftolpl = 1.e-10; */
12695: double age, agebase, agelim;
12696: double tot;
1.218 brouard 12697: /* double ***mobaverage; */
12698: /* double **dnewm, **doldm, **dsavm; /\* for use *\/ */
1.217 brouard 12699:
12700: strcpy(fileresplb,"PLB_");
12701: strcat(fileresplb,fileresu);
12702: if((ficresplb=fopen(fileresplb,"w"))==NULL) {
1.288 brouard 12703: printf("Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
12704: fprintf(ficlog,"Problem with backward prevalence resultfile: %s\n", fileresplb);return 1;
1.217 brouard 12705: }
1.288 brouard 12706: printf("Computing backward prevalence: result on file '%s' \n", fileresplb);
12707: fprintf(ficlog,"Computing backward prevalence: result on file '%s' \n", fileresplb);
1.217 brouard 12708: pstamp(ficresplb);
1.288 brouard 12709: fprintf(ficresplb,"# Backward prevalence. Precision given by ftolpl=%g \n", ftolpl);
1.217 brouard 12710: fprintf(ficresplb,"#Age ");
12711: for(i=1; i<=nlstate;i++) fprintf(ficresplb,"%d-%d ",i,i);
12712: fprintf(ficresplb,"\n");
12713:
1.218 brouard 12714:
12715: /* prlim=matrix(1,nlstate,1,nlstate);*/ /* back in main */
12716:
12717: agebase=ageminpar;
12718: agelim=agemaxpar;
12719:
12720:
1.227 brouard 12721: i1=pow(2,cptcoveff);
1.218 brouard 12722: if (cptcovn < 1){i1=1;}
1.227 brouard 12723:
1.238 brouard 12724: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.338 brouard 12725: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12726: k=TKresult[nres];
12727: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
12728: /* if(i1 != 1 && TKresult[nres]!= k) */
12729: /* continue; */
12730: /* /\*printf("cptcov=%d cptcod=%d codtab=%d\n",cptcov, cptcod,codtabm(cptcod,cptcov));*\/ */
1.238 brouard 12731: fprintf(ficresplb,"#******");
12732: printf("#******");
12733: fprintf(ficlog,"#******");
1.338 brouard 12734: for(j=1;j<=cptcovs ;j++) {/**< cptcovs number of SIMPLE covariates in the model or resultline V2+V1 =2 (dummy or quantit or time varying) */
12735: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12736: fprintf(ficresplb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12737: fprintf(ficlog," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12738: }
1.338 brouard 12739: /* for(j=1;j<=cptcoveff ;j++) {/\* all covariates *\/ */
12740: /* fprintf(ficresplb," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12741: /* printf(" V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12742: /* fprintf(ficlog," V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12743: /* } */
12744: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12745: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12746: /* fprintf(ficresplb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12747: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12748: /* } */
1.238 brouard 12749: fprintf(ficresplb,"******\n");
12750: printf("******\n");
12751: fprintf(ficlog,"******\n");
12752: if(invalidvarcomb[k]){
12753: printf("\nCombination (%d) ignored because no cases \n",k);
12754: fprintf(ficresplb,"#Combination (%d) ignored because no cases \n",k);
12755: fprintf(ficlog,"\nCombination (%d) ignored because no cases \n",k);
12756: continue;
12757: }
1.218 brouard 12758:
1.238 brouard 12759: fprintf(ficresplb,"#Age ");
1.338 brouard 12760: for(j=1;j<=cptcovs;j++) {
12761: fprintf(ficresplb,"V%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12762: }
12763: for(i=1; i<=nlstate;i++) fprintf(ficresplb," %d-%d ",i,i);
12764: fprintf(ficresplb,"Total Years_to_converge\n");
1.218 brouard 12765:
12766:
1.238 brouard 12767: for (age=agebase; age<=agelim; age++){
12768: /* for (age=agebase; age<=agebase; age++){ */
12769: if(mobilavproj > 0){
12770: /* bprevalim(bprlim, mobaverage, nlstate, p, age, ageminpar, agemaxpar, oldm, savm, doldm, dsavm, ftolpl, ncvyearp, k); */
12771: /* bprevalim(bprlim, mobaverage, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12772: bprevalim(bprlim, mobaverage, nlstate, p, age, ftolpl, ncvyearp, k, nres);
1.238 brouard 12773: }else if (mobilavproj == 0){
12774: printf("There is no chance to get back prevalence limit if data aren't non zero and summing to 1, please try a non null mobil_average(=%d) parameter or mobil_average=-1 if you want to try at your own risk.\n",mobilavproj);
12775: fprintf(ficlog,"There is no chance to get back prevalence limit if data aren't non zero and summing to 1, please try a non null mobil_average(=%d) parameter or mobil_average=-1 if you want to try at your own risk.\n",mobilavproj);
12776: exit(1);
12777: }else{
12778: /* bprevalim(bprlim, probs, nlstate, p, age, oldm, savm, dnewm, doldm, dsavm, ftolpl, ncvyearp, k); */
1.242 brouard 12779: bprevalim(bprlim, probs, nlstate, p, age, ftolpl, ncvyearp, k,nres);
1.266 brouard 12780: /* printf("TOTOT\n"); */
12781: /* exit(1); */
1.238 brouard 12782: }
12783: fprintf(ficresplb,"%.0f ",age );
1.338 brouard 12784: for(j=1;j<=cptcovs;j++)
12785: fprintf(ficresplb,"%d %lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.238 brouard 12786: tot=0.;
12787: for(i=1; i<=nlstate;i++){
12788: tot += bprlim[i][i];
12789: fprintf(ficresplb," %.5f", bprlim[i][i]);
12790: }
12791: fprintf(ficresplb," %.3f %d\n", tot, *ncvyearp);
12792: } /* Age */
12793: /* was end of cptcod */
1.255 brouard 12794: /*fprintf(ficresplb,"\n");*/ /* Seems to be necessary for gnuplot only if two result lines and no covariate. */
1.338 brouard 12795: /* } /\* end of any combination *\/ */
1.238 brouard 12796: } /* end of nres */
1.218 brouard 12797: /* hBijx(p, bage, fage); */
12798: /* fclose(ficrespijb); */
12799:
12800: return 0;
1.217 brouard 12801: }
1.218 brouard 12802:
1.180 brouard 12803: int hPijx(double *p, int bage, int fage){
12804: /*------------- h Pij x at various ages ------------*/
1.336 brouard 12805: /* to be optimized with precov */
1.180 brouard 12806: int stepsize;
12807: int agelim;
12808: int hstepm;
12809: int nhstepm;
1.235 brouard 12810: int h, i, i1, j, k, k4, nres=0;
1.180 brouard 12811:
12812: double agedeb;
12813: double ***p3mat;
12814:
1.337 brouard 12815: strcpy(filerespij,"PIJ_"); strcat(filerespij,fileresu);
12816: if((ficrespij=fopen(filerespij,"w"))==NULL) {
12817: printf("Problem with Pij resultfile: %s\n", filerespij); return 1;
12818: fprintf(ficlog,"Problem with Pij resultfile: %s\n", filerespij); return 1;
12819: }
12820: printf("Computing pij: result on file '%s' \n", filerespij);
12821: fprintf(ficlog,"Computing pij: result on file '%s' \n", filerespij);
12822:
12823: stepsize=(int) (stepm+YEARM-1)/YEARM;
12824: /*if (stepm<=24) stepsize=2;*/
12825:
12826: agelim=AGESUP;
12827: hstepm=stepsize*YEARM; /* Every year of age */
12828: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12829:
12830: /* hstepm=1; aff par mois*/
12831: pstamp(ficrespij);
12832: fprintf(ficrespij,"#****** h Pij x Probability to be in state j at age x+h being in i at x ");
12833: i1= pow(2,cptcoveff);
12834: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12835: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12836: /* k=k+1; */
12837: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
12838: k=TKresult[nres];
1.338 brouard 12839: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12840: /* for(k=1; k<=i1;k++){ */
12841: /* if(i1 != 1 && TKresult[nres]!= k) */
12842: /* continue; */
12843: fprintf(ficrespij,"\n#****** ");
12844: for(j=1;j<=cptcovs;j++){
12845: fprintf(ficrespij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
12846: /* fprintf(ficrespij,"@wV%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12847: /* for (k4=1; k4<= nsq; k4++){ /\* For each selected (single) quantitative value *\/ */
12848: /* printf(" V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12849: /* fprintf(ficrespij," V%d=%f ",Tvqresult[nres][k4],Tqresult[nres][k4]); */
12850: }
12851: fprintf(ficrespij,"******\n");
12852:
12853: for (agedeb=fage; agedeb>=bage; agedeb--){ /* If stepm=6 months */
12854: nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /* Typically 20 years = 20*12/6=40 */
12855: nhstepm = nhstepm/hstepm; /* Typically 40/4=10 */
12856:
12857: /* nhstepm=nhstepm*YEARM; aff par mois*/
12858:
12859: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12860: oldm=oldms;savm=savms;
12861: hpxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k, nres);
12862: fprintf(ficrespij,"# Cov Agex agex+h hpijx with i,j=");
12863: for(i=1; i<=nlstate;i++)
12864: for(j=1; j<=nlstate+ndeath;j++)
12865: fprintf(ficrespij," %1d-%1d",i,j);
12866: fprintf(ficrespij,"\n");
12867: for (h=0; h<=nhstepm; h++){
12868: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12869: fprintf(ficrespij,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm );
1.183 brouard 12870: for(i=1; i<=nlstate;i++)
12871: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12872: fprintf(ficrespij," %.5f", p3mat[i][j][h]);
1.183 brouard 12873: fprintf(ficrespij,"\n");
12874: }
1.337 brouard 12875: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12876: fprintf(ficrespij,"\n");
1.180 brouard 12877: }
1.337 brouard 12878: }
12879: /*}*/
12880: return 0;
1.180 brouard 12881: }
1.218 brouard 12882:
12883: int hBijx(double *p, int bage, int fage, double ***prevacurrent){
1.217 brouard 12884: /*------------- h Bij x at various ages ------------*/
1.336 brouard 12885: /* To be optimized with precov */
1.217 brouard 12886: int stepsize;
1.218 brouard 12887: /* int agelim; */
12888: int ageminl;
1.217 brouard 12889: int hstepm;
12890: int nhstepm;
1.238 brouard 12891: int h, i, i1, j, k, nres;
1.218 brouard 12892:
1.217 brouard 12893: double agedeb;
12894: double ***p3mat;
1.218 brouard 12895:
12896: strcpy(filerespijb,"PIJB_"); strcat(filerespijb,fileresu);
12897: if((ficrespijb=fopen(filerespijb,"w"))==NULL) {
12898: printf("Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12899: fprintf(ficlog,"Problem with Pij back resultfile: %s\n", filerespijb); return 1;
12900: }
12901: printf("Computing pij back: result on file '%s' \n", filerespijb);
12902: fprintf(ficlog,"Computing pij back: result on file '%s' \n", filerespijb);
12903:
12904: stepsize=(int) (stepm+YEARM-1)/YEARM;
12905: /*if (stepm<=24) stepsize=2;*/
1.217 brouard 12906:
1.218 brouard 12907: /* agelim=AGESUP; */
1.289 brouard 12908: ageminl=AGEINF; /* was 30 */
1.218 brouard 12909: hstepm=stepsize*YEARM; /* Every year of age */
12910: hstepm=hstepm/stepm; /* Typically 2 years, = 2/6 months = 4 */
12911:
12912: /* hstepm=1; aff par mois*/
12913: pstamp(ficrespijb);
1.255 brouard 12914: fprintf(ficrespijb,"#****** h Bij x Back probability to be in state i at age x-h being in j at x: B1j+B2j+...=1 ");
1.227 brouard 12915: i1= pow(2,cptcoveff);
1.218 brouard 12916: /* for(cptcov=1,k=0;cptcov<=i1;cptcov++){ */
12917: /* /\*for(cptcod=1;cptcod<=ncodemax[cptcov];cptcod++){*\/ */
12918: /* k=k+1; */
1.238 brouard 12919: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
1.337 brouard 12920: k=TKresult[nres];
1.338 brouard 12921: if(TKresult[nres]==0) k=1; /* To be checked for noresult */
1.337 brouard 12922: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
12923: /* if(i1 != 1 && TKresult[nres]!= k) */
12924: /* continue; */
12925: fprintf(ficrespijb,"\n#****** ");
12926: for(j=1;j<=cptcovs;j++){
1.338 brouard 12927: fprintf(ficrespijb," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
1.337 brouard 12928: /* for(j=1;j<=cptcoveff;j++) */
12929: /* fprintf(ficrespijb,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
12930: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
12931: /* fprintf(ficrespijb," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
12932: }
12933: fprintf(ficrespijb,"******\n");
12934: if(invalidvarcomb[k]){ /* Is it necessary here? */
12935: fprintf(ficrespijb,"\n#Combination (%d) ignored because no cases \n",k);
12936: continue;
12937: }
12938:
12939: /* for (agedeb=fage; agedeb>=bage; agedeb--){ /\* If stepm=6 months *\/ */
12940: for (agedeb=bage; agedeb<=fage; agedeb++){ /* If stepm=6 months and estepm=24 (2 years) */
12941: /* nhstepm=(int) rint((agelim-agedeb)*YEARM/stepm); /\* Typically 20 years = 20*12/6=40 *\/ */
12942: nhstepm=(int) rint((agedeb-ageminl)*YEARM/stepm+0.1)-1; /* Typically 20 years = 20*12/6=40 or 55*12/24=27.5-1.1=>27 */
12943: nhstepm = nhstepm/hstepm; /* Typically 40/4=10, because estepm=24 stepm=6 => hstepm=24/6=4 or 28*/
12944:
12945: /* nhstepm=nhstepm*YEARM; aff par mois*/
12946:
12947: p3mat=ma3x(1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm); /* We can't have it at an upper level because of nhstepm */
12948: /* and memory limitations if stepm is small */
12949:
12950: /* oldm=oldms;savm=savms; */
12951: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,nlstate,stepm,oldm,savm, k); */
12952: hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm, k, nres);/* Bug valgrind */
12953: /* hbxij(p3mat,nhstepm,agedeb,hstepm,p,prevacurrent,nlstate,stepm,oldm,savm, dnewm, doldm, dsavm, k); */
12954: fprintf(ficrespijb,"# Cov Agex agex-h hbijx with i,j=");
12955: for(i=1; i<=nlstate;i++)
12956: for(j=1; j<=nlstate+ndeath;j++)
12957: fprintf(ficrespijb," %1d-%1d",i,j);
12958: fprintf(ficrespijb,"\n");
12959: for (h=0; h<=nhstepm; h++){
12960: /*agedebphstep = agedeb + h*hstepm/YEARM*stepm;*/
12961: fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb - h*hstepm/YEARM*stepm );
12962: /* fprintf(ficrespijb,"%d %3.f %3.f",k, agedeb, agedeb + h*hstepm/YEARM*stepm ); */
1.217 brouard 12963: for(i=1; i<=nlstate;i++)
12964: for(j=1; j<=nlstate+ndeath;j++)
1.337 brouard 12965: fprintf(ficrespijb," %.5f", p3mat[i][j][h]);/* Bug valgrind */
1.217 brouard 12966: fprintf(ficrespijb,"\n");
1.337 brouard 12967: }
12968: free_ma3x(p3mat,1,nlstate+ndeath,1, nlstate+ndeath, 0,nhstepm);
12969: fprintf(ficrespijb,"\n");
12970: } /* end age deb */
12971: /* } /\* end combination *\/ */
1.238 brouard 12972: } /* end nres */
1.218 brouard 12973: return 0;
12974: } /* hBijx */
1.217 brouard 12975:
1.180 brouard 12976:
1.136 brouard 12977: /***********************************************/
12978: /**************** Main Program *****************/
12979: /***********************************************/
12980:
12981: int main(int argc, char *argv[])
12982: {
12983: #ifdef GSL
12984: const gsl_multimin_fminimizer_type *T;
12985: size_t iteri = 0, it;
12986: int rval = GSL_CONTINUE;
12987: int status = GSL_SUCCESS;
12988: double ssval;
12989: #endif
12990: int movingaverage(double ***probs, double bage,double fage, double ***mobaverage, int mobilav);
1.290 brouard 12991: int i,j, k, iter=0,m,size=100, cptcod; /* Suppressing because nobs */
12992: /* int i,j, k, n=MAXN,iter=0,m,size=100, cptcod; */
1.209 brouard 12993: int ncvyear=0; /* Number of years needed for the period prevalence to converge */
1.164 brouard 12994: int jj, ll, li, lj, lk;
1.136 brouard 12995: int numlinepar=0; /* Current linenumber of parameter file */
1.197 brouard 12996: int num_filled;
1.136 brouard 12997: int itimes;
12998: int NDIM=2;
12999: int vpopbased=0;
1.235 brouard 13000: int nres=0;
1.258 brouard 13001: int endishere=0;
1.277 brouard 13002: int noffset=0;
1.274 brouard 13003: int ncurrv=0; /* Temporary variable */
13004:
1.164 brouard 13005: char ca[32], cb[32];
1.136 brouard 13006: /* FILE *fichtm; *//* Html File */
13007: /* FILE *ficgp;*/ /*Gnuplot File */
13008: struct stat info;
1.191 brouard 13009: double agedeb=0.;
1.194 brouard 13010:
13011: double ageminpar=AGEOVERFLOW,agemin=AGEOVERFLOW, agemaxpar=-AGEOVERFLOW, agemax=-AGEOVERFLOW;
1.219 brouard 13012: double ageminout=-AGEOVERFLOW,agemaxout=AGEOVERFLOW; /* Smaller Age range redefined after movingaverage */
1.136 brouard 13013:
1.165 brouard 13014: double fret;
1.191 brouard 13015: double dum=0.; /* Dummy variable */
1.136 brouard 13016: double ***p3mat;
1.218 brouard 13017: /* double ***mobaverage; */
1.319 brouard 13018: double wald;
1.164 brouard 13019:
1.351 brouard 13020: char line[MAXLINE], linetmp[MAXLINE];
1.197 brouard 13021: char path[MAXLINE],pathc[MAXLINE],pathcd[MAXLINE],pathtot[MAXLINE];
13022:
1.234 brouard 13023: char modeltemp[MAXLINE];
1.332 brouard 13024: char resultline[MAXLINE], resultlineori[MAXLINE];
1.230 brouard 13025:
1.136 brouard 13026: char pathr[MAXLINE], pathimach[MAXLINE];
1.164 brouard 13027: char *tok, *val; /* pathtot */
1.334 brouard 13028: /* int firstobs=1, lastobs=10; /\* nobs = lastobs-firstobs declared globally ;*\/ */
1.195 brouard 13029: int c, h , cpt, c2;
1.191 brouard 13030: int jl=0;
13031: int i1, j1, jk, stepsize=0;
1.194 brouard 13032: int count=0;
13033:
1.164 brouard 13034: int *tab;
1.136 brouard 13035: int mobilavproj=0 , prevfcast=0 ; /* moving average of prev, If prevfcast=1 prevalence projection */
1.296 brouard 13036: /* double anprojd, mprojd, jprojd; /\* For eventual projections *\/ */
13037: /* double anprojf, mprojf, jprojf; */
13038: /* double jintmean,mintmean,aintmean; */
13039: int prvforecast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
13040: int prvbackcast = 0; /* Might be 1 (date of beginning of projection is a choice or 2 is the dateintmean */
13041: double yrfproj= 10.0; /* Number of years of forward projections */
13042: double yrbproj= 10.0; /* Number of years of backward projections */
13043: int prevbcast=0; /* defined as global for mlikeli and mle, replacing backcast */
1.136 brouard 13044: int mobilav=0,popforecast=0;
1.191 brouard 13045: int hstepm=0, nhstepm=0;
1.136 brouard 13046: int agemortsup;
13047: float sumlpop=0.;
13048: double jprev1=1, mprev1=1,anprev1=2000,jprev2=1, mprev2=1,anprev2=2000;
13049: double jpyram=1, mpyram=1,anpyram=2000,jpyram1=1, mpyram1=1,anpyram1=2000;
13050:
1.191 brouard 13051: double bage=0, fage=110., age, agelim=0., agebase=0.;
1.136 brouard 13052: double ftolpl=FTOL;
13053: double **prlim;
1.217 brouard 13054: double **bprlim;
1.317 brouard 13055: double ***param; /* Matrix of parameters, param[i][j][k] param=ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel)
13056: state of origin, state of destination including death, for each covariate: constante, age, and V1 V2 etc. */
1.251 brouard 13057: double ***paramstart; /* Matrix of starting parameter values */
13058: double *p, *pstart; /* p=param[1][1] pstart is for starting values guessed by freqsummary */
1.136 brouard 13059: double **matcov; /* Matrix of covariance */
1.203 brouard 13060: double **hess; /* Hessian matrix */
1.136 brouard 13061: double ***delti3; /* Scale */
13062: double *delti; /* Scale */
13063: double ***eij, ***vareij;
13064: double **varpl; /* Variances of prevalence limits by age */
1.269 brouard 13065:
1.136 brouard 13066: double *epj, vepp;
1.164 brouard 13067:
1.273 brouard 13068: double dateprev1, dateprev2;
1.296 brouard 13069: double jproj1=1,mproj1=1,anproj1=2000,jproj2=1,mproj2=1,anproj2=2000, dateproj1=0, dateproj2=0, dateprojd=0, dateprojf=0;
13070: double jback1=1,mback1=1,anback1=2000,jback2=1,mback2=1,anback2=2000, dateback1=0, dateback2=0, datebackd=0, datebackf=0;
13071:
1.217 brouard 13072:
1.136 brouard 13073: double **ximort;
1.145 brouard 13074: char *alph[]={"a","a","b","c","d","e"}, str[4]="1234";
1.136 brouard 13075: int *dcwave;
13076:
1.164 brouard 13077: char z[1]="c";
1.136 brouard 13078:
13079: /*char *strt;*/
13080: char strtend[80];
1.126 brouard 13081:
1.164 brouard 13082:
1.126 brouard 13083: /* setlocale (LC_ALL, ""); */
13084: /* bindtextdomain (PACKAGE, LOCALEDIR); */
13085: /* textdomain (PACKAGE); */
13086: /* setlocale (LC_CTYPE, ""); */
13087: /* setlocale (LC_MESSAGES, ""); */
13088:
13089: /* gettimeofday(&start_time, (struct timezone*)0); */ /* at first time */
1.157 brouard 13090: rstart_time = time(NULL);
13091: /* (void) gettimeofday(&start_time,&tzp);*/
13092: start_time = *localtime(&rstart_time);
1.126 brouard 13093: curr_time=start_time;
1.157 brouard 13094: /*tml = *localtime(&start_time.tm_sec);*/
13095: /* strcpy(strstart,asctime(&tml)); */
13096: strcpy(strstart,asctime(&start_time));
1.126 brouard 13097:
13098: /* printf("Localtime (at start)=%s",strstart); */
1.157 brouard 13099: /* tp.tm_sec = tp.tm_sec +86400; */
13100: /* tm = *localtime(&start_time.tm_sec); */
1.126 brouard 13101: /* tmg.tm_year=tmg.tm_year +dsign*dyear; */
13102: /* tmg.tm_mon=tmg.tm_mon +dsign*dmonth; */
13103: /* tmg.tm_hour=tmg.tm_hour + 1; */
1.157 brouard 13104: /* tp.tm_sec = mktime(&tmg); */
1.126 brouard 13105: /* strt=asctime(&tmg); */
13106: /* printf("Time(after) =%s",strstart); */
13107: /* (void) time (&time_value);
13108: * printf("time=%d,t-=%d\n",time_value,time_value-86400);
13109: * tm = *localtime(&time_value);
13110: * strstart=asctime(&tm);
13111: * printf("tim_value=%d,asctime=%s\n",time_value,strstart);
13112: */
13113:
13114: nberr=0; /* Number of errors and warnings */
13115: nbwarn=0;
1.184 brouard 13116: #ifdef WIN32
13117: _getcwd(pathcd, size);
13118: #else
1.126 brouard 13119: getcwd(pathcd, size);
1.184 brouard 13120: #endif
1.191 brouard 13121: syscompilerinfo(0);
1.196 brouard 13122: printf("\nIMaCh version %s, %s\n%s",version, copyright, fullversion);
1.126 brouard 13123: if(argc <=1){
13124: printf("\nEnter the parameter file name: ");
1.205 brouard 13125: if(!fgets(pathr,FILENAMELENGTH,stdin)){
13126: printf("ERROR Empty parameter file name\n");
13127: goto end;
13128: }
1.126 brouard 13129: i=strlen(pathr);
13130: if(pathr[i-1]=='\n')
13131: pathr[i-1]='\0';
1.156 brouard 13132: i=strlen(pathr);
1.205 brouard 13133: if(i >= 1 && pathr[i-1]==' ') {/* This may happen when dragging on oS/X! */
1.156 brouard 13134: pathr[i-1]='\0';
1.205 brouard 13135: }
13136: i=strlen(pathr);
13137: if( i==0 ){
13138: printf("ERROR Empty parameter file name\n");
13139: goto end;
13140: }
13141: for (tok = pathr; tok != NULL; ){
1.126 brouard 13142: printf("Pathr |%s|\n",pathr);
13143: while ((val = strsep(&tok, "\"" )) != NULL && *val == '\0');
13144: printf("val= |%s| pathr=%s\n",val,pathr);
13145: strcpy (pathtot, val);
13146: if(pathr[0] == '\0') break; /* Dirty */
13147: }
13148: }
1.281 brouard 13149: else if (argc<=2){
13150: strcpy(pathtot,argv[1]);
13151: }
1.126 brouard 13152: else{
13153: strcpy(pathtot,argv[1]);
1.281 brouard 13154: strcpy(z,argv[2]);
13155: printf("\nargv[2]=%s z=%c\n",argv[2],z[0]);
1.126 brouard 13156: }
13157: /*if(getcwd(pathcd, MAXLINE)!= NULL)printf ("Error pathcd\n");*/
13158: /*cygwin_split_path(pathtot,path,optionfile);
13159: printf("pathtot=%s, path=%s, optionfile=%s\n",pathtot,path,optionfile);*/
13160: /* cutv(path,optionfile,pathtot,'\\');*/
13161:
13162: /* Split argv[0], imach program to get pathimach */
13163: printf("\nargv[0]=%s argv[1]=%s, \n",argv[0],argv[1]);
13164: split(argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13165: printf("\nargv[0]=%s pathimach=%s, \noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",argv[0],pathimach,optionfile,optionfilext,optionfilefiname);
13166: /* strcpy(pathimach,argv[0]); */
13167: /* Split argv[1]=pathtot, parameter file name to get path, optionfile, extension and name */
13168: split(pathtot,path,optionfile,optionfilext,optionfilefiname);
13169: printf("\npathtot=%s,\npath=%s,\noptionfile=%s \noptionfilext=%s \noptionfilefiname=%s\n",pathtot,path,optionfile,optionfilext,optionfilefiname);
1.184 brouard 13170: #ifdef WIN32
13171: _chdir(path); /* Can be a relative path */
13172: if(_getcwd(pathcd,MAXLINE) > 0) /* So pathcd is the full path */
13173: #else
1.126 brouard 13174: chdir(path); /* Can be a relative path */
1.184 brouard 13175: if (getcwd(pathcd, MAXLINE) > 0) /* So pathcd is the full path */
13176: #endif
13177: printf("Current directory %s!\n",pathcd);
1.126 brouard 13178: strcpy(command,"mkdir ");
13179: strcat(command,optionfilefiname);
13180: if((outcmd=system(command)) != 0){
1.169 brouard 13181: printf("Directory already exists (or can't create it) %s%s, err=%d\n",path,optionfilefiname,outcmd);
1.126 brouard 13182: /* fprintf(ficlog,"Problem creating directory %s%s\n",path,optionfilefiname); */
13183: /* fclose(ficlog); */
13184: /* exit(1); */
13185: }
13186: /* if((imk=mkdir(optionfilefiname))<0){ */
13187: /* perror("mkdir"); */
13188: /* } */
13189:
13190: /*-------- arguments in the command line --------*/
13191:
1.186 brouard 13192: /* Main Log file */
1.126 brouard 13193: strcat(filelog, optionfilefiname);
13194: strcat(filelog,".log"); /* */
13195: if((ficlog=fopen(filelog,"w"))==NULL) {
13196: printf("Problem with logfile %s\n",filelog);
13197: goto end;
13198: }
13199: fprintf(ficlog,"Log filename:%s\n",filelog);
1.197 brouard 13200: fprintf(ficlog,"Version %s %s",version,fullversion);
1.126 brouard 13201: fprintf(ficlog,"\nEnter the parameter file name: \n");
13202: fprintf(ficlog,"pathimach=%s\npathtot=%s\n\
13203: path=%s \n\
13204: optionfile=%s\n\
13205: optionfilext=%s\n\
1.156 brouard 13206: optionfilefiname='%s'\n",pathimach,pathtot,path,optionfile,optionfilext,optionfilefiname);
1.126 brouard 13207:
1.197 brouard 13208: syscompilerinfo(1);
1.167 brouard 13209:
1.126 brouard 13210: printf("Local time (at start):%s",strstart);
13211: fprintf(ficlog,"Local time (at start): %s",strstart);
13212: fflush(ficlog);
13213: /* (void) gettimeofday(&curr_time,&tzp); */
1.157 brouard 13214: /* printf("Elapsed time %d\n", asc_diff_time(curr_time.tm_sec-start_time.tm_sec,tmpout)); */
1.126 brouard 13215:
13216: /* */
13217: strcpy(fileres,"r");
13218: strcat(fileres, optionfilefiname);
1.201 brouard 13219: strcat(fileresu, optionfilefiname); /* Without r in front */
1.126 brouard 13220: strcat(fileres,".txt"); /* Other files have txt extension */
1.201 brouard 13221: strcat(fileresu,".txt"); /* Other files have txt extension */
1.126 brouard 13222:
1.186 brouard 13223: /* Main ---------arguments file --------*/
1.126 brouard 13224:
13225: if((ficpar=fopen(optionfile,"r"))==NULL) {
1.155 brouard 13226: printf("Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
13227: fprintf(ficlog,"Problem with optionfile '%s' with errno='%s'\n",optionfile,strerror(errno));
1.126 brouard 13228: fflush(ficlog);
1.149 brouard 13229: /* goto end; */
13230: exit(70);
1.126 brouard 13231: }
13232:
13233: strcpy(filereso,"o");
1.201 brouard 13234: strcat(filereso,fileresu);
1.126 brouard 13235: if((ficparo=fopen(filereso,"w"))==NULL) { /* opened on subdirectory */
13236: printf("Problem with Output resultfile: %s\n", filereso);
13237: fprintf(ficlog,"Problem with Output resultfile: %s\n", filereso);
13238: fflush(ficlog);
13239: goto end;
13240: }
1.278 brouard 13241: /*-------- Rewriting parameter file ----------*/
13242: strcpy(rfileres,"r"); /* "Rparameterfile */
13243: strcat(rfileres,optionfilefiname); /* Parameter file first name */
13244: strcat(rfileres,"."); /* */
13245: strcat(rfileres,optionfilext); /* Other files have txt extension */
13246: if((ficres =fopen(rfileres,"w"))==NULL) {
13247: printf("Problem writing new parameter file: %s\n", rfileres);goto end;
13248: fprintf(ficlog,"Problem writing new parameter file: %s\n", rfileres);goto end;
13249: fflush(ficlog);
13250: goto end;
13251: }
13252: fprintf(ficres,"#IMaCh %s\n",version);
1.126 brouard 13253:
1.278 brouard 13254:
1.126 brouard 13255: /* Reads comments: lines beginning with '#' */
13256: numlinepar=0;
1.277 brouard 13257: /* Is it a BOM UTF-8 Windows file? */
13258: /* First parameter line */
1.197 brouard 13259: while(fgets(line, MAXLINE, ficpar)) {
1.277 brouard 13260: noffset=0;
13261: if( line[0] == (char)0xEF && line[1] == (char)0xBB) /* EF BB BF */
13262: {
13263: noffset=noffset+3;
13264: printf("# File is an UTF8 Bom.\n"); // 0xBF
13265: }
1.302 brouard 13266: /* else if( line[0] == (char)0xFE && line[1] == (char)0xFF)*/
13267: else if( line[0] == (char)0xFF && line[1] == (char)0xFE)
1.277 brouard 13268: {
13269: noffset=noffset+2;
13270: printf("# File is an UTF16BE BOM file\n");
13271: }
13272: else if( line[0] == 0 && line[1] == 0)
13273: {
13274: if( line[2] == (char)0xFE && line[3] == (char)0xFF){
13275: noffset=noffset+4;
13276: printf("# File is an UTF16BE BOM file\n");
13277: }
13278: } else{
13279: ;/*printf(" Not a BOM file\n");*/
13280: }
13281:
1.197 brouard 13282: /* If line starts with a # it is a comment */
1.277 brouard 13283: if (line[noffset] == '#') {
1.197 brouard 13284: numlinepar++;
13285: fputs(line,stdout);
13286: fputs(line,ficparo);
1.278 brouard 13287: fputs(line,ficres);
1.197 brouard 13288: fputs(line,ficlog);
13289: continue;
13290: }else
13291: break;
13292: }
13293: if((num_filled=sscanf(line,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", \
13294: title, datafile, &lastobs, &firstpass,&lastpass)) !=EOF){
13295: if (num_filled != 5) {
13296: printf("Should be 5 parameters\n");
1.283 brouard 13297: fprintf(ficlog,"Should be 5 parameters\n");
1.197 brouard 13298: }
1.126 brouard 13299: numlinepar++;
1.197 brouard 13300: printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.283 brouard 13301: fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13302: fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
13303: fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\n", title, datafile, lastobs, firstpass,lastpass);
1.197 brouard 13304: }
13305: /* Second parameter line */
13306: while(fgets(line, MAXLINE, ficpar)) {
1.283 brouard 13307: /* while(fscanf(ficpar,"%[^\n]", line)) { */
13308: /* If line starts with a # it is a comment. Strangely fgets reads the EOL and fputs doesn't */
1.197 brouard 13309: if (line[0] == '#') {
13310: numlinepar++;
1.283 brouard 13311: printf("%s",line);
13312: fprintf(ficres,"%s",line);
13313: fprintf(ficparo,"%s",line);
13314: fprintf(ficlog,"%s",line);
1.197 brouard 13315: continue;
13316: }else
13317: break;
13318: }
1.223 brouard 13319: if((num_filled=sscanf(line,"ftol=%lf stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n", \
13320: &ftol, &stepm, &ncovcol, &nqv, &ntv, &nqtv, &nlstate, &ndeath, &maxwav, &mle, &weightopt)) !=EOF){
13321: if (num_filled != 11) {
13322: printf("Not 11 parameters, for example:ftol=1.e-8 stepm=12 ncovcol=2 nqv=1 ntv=2 nqtv=1 nlstate=2 ndeath=1 maxwav=3 mle=1 weight=1\n");
1.209 brouard 13323: printf("but line=%s\n",line);
1.283 brouard 13324: fprintf(ficlog,"Not 11 parameters, for example:ftol=1.e-8 stepm=12 ncovcol=2 nqv=1 ntv=2 nqtv=1 nlstate=2 ndeath=1 maxwav=3 mle=1 weight=1\n");
13325: fprintf(ficlog,"but line=%s\n",line);
1.197 brouard 13326: }
1.286 brouard 13327: if( lastpass > maxwav){
13328: printf("Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13329: fprintf(ficlog,"Error (lastpass = %d) > (maxwav = %d)\n",lastpass, maxwav);
13330: fflush(ficlog);
13331: goto end;
13332: }
13333: printf("ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
1.283 brouard 13334: fprintf(ficparo,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
1.286 brouard 13335: fprintf(ficres,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, 0, weightopt);
1.283 brouard 13336: fprintf(ficlog,"ftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\n",ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, mle, weightopt);
1.126 brouard 13337: }
1.203 brouard 13338: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
1.209 brouard 13339: /*ftolpl=6.e-4; *//* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
1.197 brouard 13340: /* Third parameter line */
13341: while(fgets(line, MAXLINE, ficpar)) {
13342: /* If line starts with a # it is a comment */
13343: if (line[0] == '#') {
13344: numlinepar++;
1.283 brouard 13345: printf("%s",line);
13346: fprintf(ficres,"%s",line);
13347: fprintf(ficparo,"%s",line);
13348: fprintf(ficlog,"%s",line);
1.197 brouard 13349: continue;
13350: }else
13351: break;
13352: }
1.351 brouard 13353: if((num_filled=sscanf(line,"model=%[^.\n]", model)) !=EOF){ /* Every character after model but dot and return */
13354: if (num_filled != 1){
13355: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13356: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13357: model[0]='\0';
13358: goto end;
13359: }else{
13360: trimbtab(linetmp,line); /* Trims multiple blanks in line */
13361: strcpy(line, linetmp);
13362: }
13363: }
13364: if((num_filled=sscanf(line,"model=1+age%[^.\n]", model)) !=EOF){ /* Every character after 1+age but dot and return */
1.279 brouard 13365: if (num_filled != 1){
1.302 brouard 13366: printf("ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
13367: fprintf(ficlog,"ERROR %d: Model should be at minimum 'model=1+age+' instead of '%s'\n",num_filled, line);
1.197 brouard 13368: model[0]='\0';
13369: goto end;
13370: }
13371: else{
13372: if (model[0]=='+'){
13373: for(i=1; i<=strlen(model);i++)
13374: modeltemp[i-1]=model[i];
1.201 brouard 13375: strcpy(model,modeltemp);
1.197 brouard 13376: }
13377: }
1.338 brouard 13378: /* printf(" model=1+age%s modeltemp= %s, model=1+age+%s\n",model, modeltemp, model);fflush(stdout); */
1.203 brouard 13379: printf("model=1+age+%s\n",model);fflush(stdout);
1.283 brouard 13380: fprintf(ficparo,"model=1+age+%s\n",model);fflush(stdout);
13381: fprintf(ficres,"model=1+age+%s\n",model);fflush(stdout);
13382: fprintf(ficlog,"model=1+age+%s\n",model);fflush(stdout);
1.197 brouard 13383: }
13384: /* fscanf(ficpar,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%lf stepm=%d ncovcol=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d model=1+age+%s\n",title, datafile, &lastobs, &firstpass,&lastpass,&ftol, &stepm, &ncovcol, &nlstate,&ndeath, &maxwav, &mle, &weightopt,model); */
13385: /* numlinepar=numlinepar+3; /\* In general *\/ */
13386: /* printf("title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncovcol=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\nmodel=1+age+%s\n", title, datafile, lastobs, firstpass,lastpass,ftol, stepm, ncovcol, nlstate,ndeath, maxwav, mle, weightopt,model); */
1.283 brouard 13387: /* fprintf(ficparo,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\nmodel=1+age+%s.\n", title, datafile, lastobs, firstpass,lastpass,ftol,stepm,ncovcol, nqv, ntv, nqtv, nlstate,ndeath,maxwav, mle, weightopt,model); */
13388: /* fprintf(ficlog,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle=%d weight=%d\nmodel=1+age+%s.\n", title, datafile, lastobs, firstpass,lastpass,ftol,stepm,ncovcol, nqv, ntv, nqtv, nlstate,ndeath,maxwav, mle, weightopt,model); */
1.126 brouard 13389: fflush(ficlog);
1.190 brouard 13390: /* if(model[0]=='#'|| model[0]== '\0'){ */
13391: if(model[0]=='#'){
1.279 brouard 13392: printf("Error in 'model' line: model should start with 'model=1+age+' and end without space \n \
13393: 'model=1+age+' or 'model=1+age+V1.' or 'model=1+age+age*age+V1+V1*age' or \n \
13394: 'model=1+age+V1+V2' or 'model=1+age+V1+V2+V1*V2' etc. \n"); \
1.187 brouard 13395: if(mle != -1){
1.279 brouard 13396: printf("Fix the model line and run imach with mle=-1 to get a correct template of the parameter vectors and subdiagonal covariance matrix.\n");
1.187 brouard 13397: exit(1);
13398: }
13399: }
1.126 brouard 13400: while((c=getc(ficpar))=='#' && c!= EOF){
13401: ungetc(c,ficpar);
13402: fgets(line, MAXLINE, ficpar);
13403: numlinepar++;
1.195 brouard 13404: if(line[1]=='q'){ /* This #q will quit imach (the answer is q) */
13405: z[0]=line[1];
1.342 brouard 13406: }else if(line[1]=='d'){ /* For debugging individual values of covariates in ficresilk */
1.343 brouard 13407: debugILK=1;printf("DebugILK\n");
1.195 brouard 13408: }
13409: /* printf("****line [1] = %c \n",line[1]); */
1.141 brouard 13410: fputs(line, stdout);
13411: //puts(line);
1.126 brouard 13412: fputs(line,ficparo);
13413: fputs(line,ficlog);
13414: }
13415: ungetc(c,ficpar);
13416:
13417:
1.290 brouard 13418: covar=matrix(0,NCOVMAX,firstobs,lastobs); /**< used in readdata */
13419: if(nqv>=1)coqvar=matrix(1,nqv,firstobs,lastobs); /**< Fixed quantitative covariate */
13420: if(nqtv>=1)cotqvar=ma3x(1,maxwav,1,nqtv,firstobs,lastobs); /**< Time varying quantitative covariate */
1.341 brouard 13421: /* if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,1,ntv+nqtv,firstobs,lastobs); /\**< Time varying covariate (dummy and quantitative)*\/ */
13422: if(ntv+nqtv>=1)cotvar=ma3x(1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs); /**< Might be better */
1.136 brouard 13423: cptcovn=0; /*Number of covariates, i.e. number of '+' in model statement plus one, indepently of n in Vn*/
13424: /* v1+v2+v3+v2*v4+v5*age makes cptcovn = 5
13425: v1+v2*age+v2*v3 makes cptcovn = 3
13426: */
13427: if (strlen(model)>1)
1.187 brouard 13428: ncovmodel=2+nbocc(model,'+')+1; /*Number of variables including intercept and age = cptcovn + intercept + age : v1+v2+v3+v2*v4+v5*age makes 5+2=7,age*age makes 3*/
1.145 brouard 13429: else
1.187 brouard 13430: ncovmodel=2; /* Constant and age */
1.133 brouard 13431: nforce= (nlstate+ndeath-1)*nlstate; /* Number of forces ij from state i to j */
13432: npar= nforce*ncovmodel; /* Number of parameters like aij*/
1.131 brouard 13433: if(npar >MAXPARM || nlstate >NLSTATEMAX || ndeath >NDEATHMAX || ncovmodel>NCOVMAX){
13434: printf("Too complex model for current IMaCh: npar=(nlstate+ndeath-1)*nlstate*ncovmodel=%d >= %d(MAXPARM) or nlstate=%d >= %d(NLSTATEMAX) or ndeath=%d >= %d(NDEATHMAX) or ncovmodel=(k+age+#of+signs)=%d(NCOVMAX) >= %d\n",npar, MAXPARM, nlstate, NLSTATEMAX, ndeath, NDEATHMAX, ncovmodel, NCOVMAX);
13435: fprintf(ficlog,"Too complex model for current IMaCh: %d >=%d(MAXPARM) or %d >=%d(NLSTATEMAX) or %d >=%d(NDEATHMAX) or %d(NCOVMAX) >=%d\n",npar, MAXPARM, nlstate, NLSTATEMAX, ndeath, NDEATHMAX, ncovmodel, NCOVMAX);
13436: fflush(stdout);
13437: fclose (ficlog);
13438: goto end;
13439: }
1.126 brouard 13440: delti3= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13441: delti=delti3[1][1];
13442: /*delti=vector(1,npar); *//* Scale of each paramater (output from hesscov)*/
13443: if(mle==-1){ /* Print a wizard for help writing covariance matrix */
1.247 brouard 13444: /* We could also provide initial parameters values giving by simple logistic regression
13445: * only one way, that is without matrix product. We will have nlstate maximizations */
13446: /* for(i=1;i<nlstate;i++){ */
13447: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
13448: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
13449: /* } */
1.126 brouard 13450: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.191 brouard 13451: printf(" You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
13452: fprintf(ficlog," You chose mle=-1, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13453: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
13454: fclose (ficparo);
13455: fclose (ficlog);
13456: goto end;
13457: exit(0);
1.220 brouard 13458: } else if(mle==-5) { /* Main Wizard */
1.126 brouard 13459: prwizard(ncovmodel, nlstate, ndeath, model, ficparo);
1.192 brouard 13460: printf(" You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
13461: fprintf(ficlog," You chose mle=-3, look at file %s for a template of covariance matrix \n",filereso);
1.126 brouard 13462: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
13463: matcov=matrix(1,npar,1,npar);
1.203 brouard 13464: hess=matrix(1,npar,1,npar);
1.220 brouard 13465: } else{ /* Begin of mle != -1 or -5 */
1.145 brouard 13466: /* Read guessed parameters */
1.126 brouard 13467: /* Reads comments: lines beginning with '#' */
13468: while((c=getc(ficpar))=='#' && c!= EOF){
13469: ungetc(c,ficpar);
13470: fgets(line, MAXLINE, ficpar);
13471: numlinepar++;
1.141 brouard 13472: fputs(line,stdout);
1.126 brouard 13473: fputs(line,ficparo);
13474: fputs(line,ficlog);
13475: }
13476: ungetc(c,ficpar);
13477:
13478: param= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.251 brouard 13479: paramstart= ma3x(1,nlstate,1,nlstate+ndeath-1,1,ncovmodel);
1.126 brouard 13480: for(i=1; i <=nlstate; i++){
1.234 brouard 13481: j=0;
1.126 brouard 13482: for(jj=1; jj <=nlstate+ndeath; jj++){
1.234 brouard 13483: if(jj==i) continue;
13484: j++;
1.292 brouard 13485: while((c=getc(ficpar))=='#' && c!= EOF){
13486: ungetc(c,ficpar);
13487: fgets(line, MAXLINE, ficpar);
13488: numlinepar++;
13489: fputs(line,stdout);
13490: fputs(line,ficparo);
13491: fputs(line,ficlog);
13492: }
13493: ungetc(c,ficpar);
1.234 brouard 13494: fscanf(ficpar,"%1d%1d",&i1,&j1);
13495: if ((i1 != i) || (j1 != jj)){
13496: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n \
1.126 brouard 13497: It might be a problem of design; if ncovcol and the model are correct\n \
13498: run imach with mle=-1 to get a correct template of the parameter file.\n",numlinepar, i,j, i1, j1);
1.234 brouard 13499: exit(1);
13500: }
13501: fprintf(ficparo,"%1d%1d",i1,j1);
13502: if(mle==1)
13503: printf("%1d%1d",i,jj);
13504: fprintf(ficlog,"%1d%1d",i,jj);
13505: for(k=1; k<=ncovmodel;k++){
13506: fscanf(ficpar," %lf",¶m[i][j][k]);
13507: if(mle==1){
13508: printf(" %lf",param[i][j][k]);
13509: fprintf(ficlog," %lf",param[i][j][k]);
13510: }
13511: else
13512: fprintf(ficlog," %lf",param[i][j][k]);
13513: fprintf(ficparo," %lf",param[i][j][k]);
13514: }
13515: fscanf(ficpar,"\n");
13516: numlinepar++;
13517: if(mle==1)
13518: printf("\n");
13519: fprintf(ficlog,"\n");
13520: fprintf(ficparo,"\n");
1.126 brouard 13521: }
13522: }
13523: fflush(ficlog);
1.234 brouard 13524:
1.251 brouard 13525: /* Reads parameters values */
1.126 brouard 13526: p=param[1][1];
1.251 brouard 13527: pstart=paramstart[1][1];
1.126 brouard 13528:
13529: /* Reads comments: lines beginning with '#' */
13530: while((c=getc(ficpar))=='#' && c!= EOF){
13531: ungetc(c,ficpar);
13532: fgets(line, MAXLINE, ficpar);
13533: numlinepar++;
1.141 brouard 13534: fputs(line,stdout);
1.126 brouard 13535: fputs(line,ficparo);
13536: fputs(line,ficlog);
13537: }
13538: ungetc(c,ficpar);
13539:
13540: for(i=1; i <=nlstate; i++){
13541: for(j=1; j <=nlstate+ndeath-1; j++){
1.234 brouard 13542: fscanf(ficpar,"%1d%1d",&i1,&j1);
13543: if ( (i1-i) * (j1-j) != 0){
13544: printf("Error in line parameters number %d, %1d%1d instead of %1d%1d \n",numlinepar, i,j, i1, j1);
13545: exit(1);
13546: }
13547: printf("%1d%1d",i,j);
13548: fprintf(ficparo,"%1d%1d",i1,j1);
13549: fprintf(ficlog,"%1d%1d",i1,j1);
13550: for(k=1; k<=ncovmodel;k++){
13551: fscanf(ficpar,"%le",&delti3[i][j][k]);
13552: printf(" %le",delti3[i][j][k]);
13553: fprintf(ficparo," %le",delti3[i][j][k]);
13554: fprintf(ficlog," %le",delti3[i][j][k]);
13555: }
13556: fscanf(ficpar,"\n");
13557: numlinepar++;
13558: printf("\n");
13559: fprintf(ficparo,"\n");
13560: fprintf(ficlog,"\n");
1.126 brouard 13561: }
13562: }
13563: fflush(ficlog);
1.234 brouard 13564:
1.145 brouard 13565: /* Reads covariance matrix */
1.126 brouard 13566: delti=delti3[1][1];
1.220 brouard 13567:
13568:
1.126 brouard 13569: /* free_ma3x(delti3,1,nlstate,1,nlstate+ndeath-1,1,ncovmodel); */ /* Hasn't to to freed here otherwise delti is no more allocated */
1.220 brouard 13570:
1.126 brouard 13571: /* Reads comments: lines beginning with '#' */
13572: while((c=getc(ficpar))=='#' && c!= EOF){
13573: ungetc(c,ficpar);
13574: fgets(line, MAXLINE, ficpar);
13575: numlinepar++;
1.141 brouard 13576: fputs(line,stdout);
1.126 brouard 13577: fputs(line,ficparo);
13578: fputs(line,ficlog);
13579: }
13580: ungetc(c,ficpar);
1.220 brouard 13581:
1.126 brouard 13582: matcov=matrix(1,npar,1,npar);
1.203 brouard 13583: hess=matrix(1,npar,1,npar);
1.131 brouard 13584: for(i=1; i <=npar; i++)
13585: for(j=1; j <=npar; j++) matcov[i][j]=0.;
1.220 brouard 13586:
1.194 brouard 13587: /* Scans npar lines */
1.126 brouard 13588: for(i=1; i <=npar; i++){
1.226 brouard 13589: count=fscanf(ficpar,"%1d%1d%d",&i1,&j1,&jk);
1.194 brouard 13590: if(count != 3){
1.226 brouard 13591: printf("Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13592: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13593: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13594: fprintf(ficlog,"Error! Error in parameter file %s at line %d after line starting with %1d%1d%1d\n\
1.194 brouard 13595: This is probably because your covariance matrix doesn't \n contain exactly %d lines corresponding to your model line '1+age+%s'.\n\
13596: Please run with mle=-1 to get a correct covariance matrix.\n",optionfile,numlinepar, i1,j1,jk, npar, model);
1.226 brouard 13597: exit(1);
1.220 brouard 13598: }else{
1.226 brouard 13599: if(mle==1)
13600: printf("%1d%1d%d",i1,j1,jk);
13601: }
13602: fprintf(ficlog,"%1d%1d%d",i1,j1,jk);
13603: fprintf(ficparo,"%1d%1d%d",i1,j1,jk);
1.126 brouard 13604: for(j=1; j <=i; j++){
1.226 brouard 13605: fscanf(ficpar," %le",&matcov[i][j]);
13606: if(mle==1){
13607: printf(" %.5le",matcov[i][j]);
13608: }
13609: fprintf(ficlog," %.5le",matcov[i][j]);
13610: fprintf(ficparo," %.5le",matcov[i][j]);
1.126 brouard 13611: }
13612: fscanf(ficpar,"\n");
13613: numlinepar++;
13614: if(mle==1)
1.220 brouard 13615: printf("\n");
1.126 brouard 13616: fprintf(ficlog,"\n");
13617: fprintf(ficparo,"\n");
13618: }
1.194 brouard 13619: /* End of read covariance matrix npar lines */
1.126 brouard 13620: for(i=1; i <=npar; i++)
13621: for(j=i+1;j<=npar;j++)
1.226 brouard 13622: matcov[i][j]=matcov[j][i];
1.126 brouard 13623:
13624: if(mle==1)
13625: printf("\n");
13626: fprintf(ficlog,"\n");
13627:
13628: fflush(ficlog);
13629:
13630: } /* End of mle != -3 */
1.218 brouard 13631:
1.186 brouard 13632: /* Main data
13633: */
1.290 brouard 13634: nobs=lastobs-firstobs+1; /* was = lastobs;*/
13635: /* num=lvector(1,n); */
13636: /* moisnais=vector(1,n); */
13637: /* annais=vector(1,n); */
13638: /* moisdc=vector(1,n); */
13639: /* andc=vector(1,n); */
13640: /* weight=vector(1,n); */
13641: /* agedc=vector(1,n); */
13642: /* cod=ivector(1,n); */
13643: /* for(i=1;i<=n;i++){ */
13644: num=lvector(firstobs,lastobs);
13645: moisnais=vector(firstobs,lastobs);
13646: annais=vector(firstobs,lastobs);
13647: moisdc=vector(firstobs,lastobs);
13648: andc=vector(firstobs,lastobs);
13649: weight=vector(firstobs,lastobs);
13650: agedc=vector(firstobs,lastobs);
13651: cod=ivector(firstobs,lastobs);
13652: for(i=firstobs;i<=lastobs;i++){
1.234 brouard 13653: num[i]=0;
13654: moisnais[i]=0;
13655: annais[i]=0;
13656: moisdc[i]=0;
13657: andc[i]=0;
13658: agedc[i]=0;
13659: cod[i]=0;
13660: weight[i]=1.0; /* Equal weights, 1 by default */
13661: }
1.290 brouard 13662: mint=matrix(1,maxwav,firstobs,lastobs);
13663: anint=matrix(1,maxwav,firstobs,lastobs);
1.325 brouard 13664: s=imatrix(1,maxwav+1,firstobs,lastobs); /* s[i][j] health state for wave i and individual j */
1.336 brouard 13665: /* printf("BUG ncovmodel=%d NCOVMAX=%d 2**ncovmodel=%f BUG\n",ncovmodel,NCOVMAX,pow(2,ncovmodel)); */
1.126 brouard 13666: tab=ivector(1,NCOVMAX);
1.144 brouard 13667: ncodemax=ivector(1,NCOVMAX); /* Number of code per covariate; if O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.192 brouard 13668: ncodemaxwundef=ivector(1,NCOVMAX); /* Number of code per covariate; if - 1 O and 1 only, 2**ncov; V1+V2+V3+V4=>16 */
1.126 brouard 13669:
1.136 brouard 13670: /* Reads data from file datafile */
13671: if (readdata(datafile, firstobs, lastobs, &imx)==1)
13672: goto end;
13673:
13674: /* Calculation of the number of parameters from char model */
1.234 brouard 13675: /* modelsav=V2+V1+V4+age*V3 strb=age*V3 stra=V2+V1+V4
1.137 brouard 13676: k=4 (age*V3) Tvar[k=4]= 3 (from V3) Tag[cptcovage=1]=4
13677: k=3 V4 Tvar[k=3]= 4 (from V4)
13678: k=2 V1 Tvar[k=2]= 1 (from V1)
13679: k=1 Tvar[1]=2 (from V2)
1.234 brouard 13680: */
13681:
13682: Tvar=ivector(1,NCOVMAX); /* Was 15 changed to NCOVMAX. */
13683: TvarsDind=ivector(1,NCOVMAX); /* */
1.330 brouard 13684: TnsdVar=ivector(1,NCOVMAX); /* */
1.335 brouard 13685: /* for(i=1; i<=NCOVMAX;i++) TnsdVar[i]=3; */
1.234 brouard 13686: TvarsD=ivector(1,NCOVMAX); /* */
13687: TvarsQind=ivector(1,NCOVMAX); /* */
13688: TvarsQ=ivector(1,NCOVMAX); /* */
1.232 brouard 13689: TvarF=ivector(1,NCOVMAX); /* */
13690: TvarFind=ivector(1,NCOVMAX); /* */
13691: TvarV=ivector(1,NCOVMAX); /* */
13692: TvarVind=ivector(1,NCOVMAX); /* */
13693: TvarA=ivector(1,NCOVMAX); /* */
13694: TvarAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13695: TvarFD=ivector(1,NCOVMAX); /* */
13696: TvarFDind=ivector(1,NCOVMAX); /* */
13697: TvarFQ=ivector(1,NCOVMAX); /* */
13698: TvarFQind=ivector(1,NCOVMAX); /* */
13699: TvarVD=ivector(1,NCOVMAX); /* */
13700: TvarVDind=ivector(1,NCOVMAX); /* */
13701: TvarVQ=ivector(1,NCOVMAX); /* */
13702: TvarVQind=ivector(1,NCOVMAX); /* */
1.339 brouard 13703: TvarVV=ivector(1,NCOVMAX); /* */
13704: TvarVVind=ivector(1,NCOVMAX); /* */
1.349 brouard 13705: TvarVVA=ivector(1,NCOVMAX); /* */
13706: TvarVVAind=ivector(1,NCOVMAX); /* */
13707: TvarAVVA=ivector(1,NCOVMAX); /* */
13708: TvarAVVAind=ivector(1,NCOVMAX); /* */
1.231 brouard 13709:
1.230 brouard 13710: Tvalsel=vector(1,NCOVMAX); /* */
1.233 brouard 13711: Tvarsel=ivector(1,NCOVMAX); /* */
1.226 brouard 13712: Typevar=ivector(-1,NCOVMAX); /* -1 to 2 */
13713: Fixed=ivector(-1,NCOVMAX); /* -1 to 3 */
13714: Dummy=ivector(-1,NCOVMAX); /* -1 to 3 */
1.349 brouard 13715: DummyV=ivector(-1,NCOVMAX); /* 1 to 3 */
13716: FixedV=ivector(-1,NCOVMAX); /* 1 to 3 */
13717:
1.137 brouard 13718: /* V2+V1+V4+age*V3 is a model with 4 covariates (3 plus signs).
13719: For each model-covariate stores the data-covariate id. Tvar[1]=2, Tvar[2]=1, Tvar[3]=4,
13720: Tvar[4=age*V3] is 3 and 'age' is recorded in Tage.
13721: */
13722: /* For model-covariate k tells which data-covariate to use but
13723: because this model-covariate is a construction we invent a new column
13724: ncovcol + k1
13725: If already ncovcol=4 and model=V2+V1+V1*V4+age*V3
13726: Tvar[3=V1*V4]=4+1 etc */
1.227 brouard 13727: Tprod=ivector(1,NCOVMAX); /* Gives the k position of the k1 product */
13728: Tposprod=ivector(1,NCOVMAX); /* Gives the k1 product from the k position */
1.137 brouard 13729: /* Tprod[k1=1]=3(=V1*V4) for V2+V1+V1*V4+age*V3
13730: if V2+V1+V1*V4+age*V3+V3*V2 TProd[k1=2]=5 (V3*V2)
1.227 brouard 13731: Tposprod[k]=k1 , Tposprod[3]=1, Tposprod[5]=2
1.137 brouard 13732: */
1.145 brouard 13733: Tvaraff=ivector(1,NCOVMAX); /* Unclear */
13734: Tvard=imatrix(1,NCOVMAX,1,2); /* n=Tvard[k1][1] and m=Tvard[k1][2] gives the couple n,m of the k1 th product Vn*Vm
1.141 brouard 13735: * For V3*V2 (in V2+V1+V1*V4+age*V3+V3*V2), V3*V2 position is 2nd.
13736: * Tvard[k1=2][1]=3 (V3) Tvard[k1=2][2]=2(V2) */
1.351 brouard 13737: Tvardk=imatrix(0,NCOVMAX,1,2);
1.145 brouard 13738: Tage=ivector(1,NCOVMAX); /* Gives the covariate id of covariates associated with age: V2 + V1 + age*V4 + V3*age
1.137 brouard 13739: 4 covariates (3 plus signs)
13740: Tage[1=V3*age]= 4; Tage[2=age*V4] = 3
1.328 brouard 13741: */
13742: for(i=1;i<NCOVMAX;i++)
13743: Tage[i]=0;
1.230 brouard 13744: Tmodelind=ivector(1,NCOVMAX);/** gives the k model position of an
1.227 brouard 13745: * individual dummy, fixed or varying:
13746: * Tmodelind[Tvaraff[3]]=9,Tvaraff[1]@9={4,
13747: * 3, 1, 0, 0, 0, 0, 0, 0},
1.230 brouard 13748: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1 ,
13749: * V1 df, V2 qf, V3 & V4 dv, V5 qv
13750: * Tmodelind[1]@9={9,0,3,2,}*/
13751: TmodelInvind=ivector(1,NCOVMAX); /* TmodelInvind=Tvar[k]- ncovcol-nqv={5-2-1=2,*/
13752: TmodelInvQind=ivector(1,NCOVMAX);/** gives the k model position of an
1.228 brouard 13753: * individual quantitative, fixed or varying:
13754: * Tmodelqind[1]=1,Tvaraff[1]@9={4,
13755: * 3, 1, 0, 0, 0, 0, 0, 0},
13756: * model=V5+V4+V3+V4*V3+V5*age+V2+V1*V2+V1*age+V1*/
1.349 brouard 13757:
13758: /* Probably useless zeroes */
13759: for(i=1;i<NCOVMAX;i++){
13760: DummyV[i]=0;
13761: FixedV[i]=0;
13762: }
13763:
13764: for(i=1; i <=ncovcol;i++){
13765: DummyV[i]=0;
13766: FixedV[i]=0;
13767: }
13768: for(i=ncovcol+1; i <=ncovcol+nqv;i++){
13769: DummyV[i]=1;
13770: FixedV[i]=0;
13771: }
13772: for(i=ncovcol+nqv+1; i <=ncovcol+nqv+ntv;i++){
13773: DummyV[i]=0;
13774: FixedV[i]=1;
13775: }
13776: for(i=ncovcol+nqv+ntv+1; i <=ncovcol+nqv+ntv+nqtv;i++){
13777: DummyV[i]=1;
13778: FixedV[i]=1;
13779: }
13780: for(i=1; i <=ncovcol+nqv+ntv+nqtv;i++){
13781: printf("Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
13782: fprintf(ficlog,"Covariate type in the data: V%d, DummyV(V%d)=%d, FixedV(V%d)=%d\n",i,i,DummyV[i],i,FixedV[i]);
13783: }
13784:
13785:
13786:
1.186 brouard 13787: /* Main decodemodel */
13788:
1.187 brouard 13789:
1.223 brouard 13790: if(decodemodel(model, lastobs) == 1) /* In order to get Tvar[k] V4+V3+V5 p Tvar[1]@3 = {4, 3, 5}*/
1.136 brouard 13791: goto end;
13792:
1.137 brouard 13793: if((double)(lastobs-imx)/(double)imx > 1.10){
13794: nbwarn++;
13795: printf("Warning: The value of parameter lastobs=%d is big compared to the \n effective number of cases imx=%d, please adjust, \n otherwise you are allocating more memory than necessary.\n",lastobs, imx);
13796: fprintf(ficlog,"Warning: The value of parameter lastobs=%d is big compared to the \n effective number of cases imx=%d, please adjust, \n otherwise you are allocating more memory than necessary.\n",lastobs, imx);
13797: }
1.136 brouard 13798: /* if(mle==1){*/
1.137 brouard 13799: if (weightopt != 1) { /* Maximisation without weights. We can have weights different from 1 but want no weight*/
13800: for(i=1;i<=imx;i++) weight[i]=1.0; /* changed to imx */
1.136 brouard 13801: }
13802:
13803: /*-calculation of age at interview from date of interview and age at death -*/
13804: agev=matrix(1,maxwav,1,imx);
13805:
13806: if(calandcheckages(imx, maxwav, &agemin, &agemax, &nberr, &nbwarn) == 1)
13807: goto end;
13808:
1.126 brouard 13809:
1.136 brouard 13810: agegomp=(int)agemin;
1.290 brouard 13811: free_vector(moisnais,firstobs,lastobs);
13812: free_vector(annais,firstobs,lastobs);
1.126 brouard 13813: /* free_matrix(mint,1,maxwav,1,n);
13814: free_matrix(anint,1,maxwav,1,n);*/
1.215 brouard 13815: /* free_vector(moisdc,1,n); */
13816: /* free_vector(andc,1,n); */
1.145 brouard 13817: /* */
13818:
1.126 brouard 13819: wav=ivector(1,imx);
1.214 brouard 13820: /* dh=imatrix(1,lastpass-firstpass+1,1,imx); */
13821: /* bh=imatrix(1,lastpass-firstpass+1,1,imx); */
13822: /* mw=imatrix(1,lastpass-firstpass+1,1,imx); */
13823: dh=imatrix(1,lastpass-firstpass+2,1,imx); /* We are adding a wave if status is unknown at last wave but death occurs after last wave.*/
13824: bh=imatrix(1,lastpass-firstpass+2,1,imx);
13825: mw=imatrix(1,lastpass-firstpass+2,1,imx);
1.126 brouard 13826:
13827: /* Concatenates waves */
1.214 brouard 13828: /* Concatenates waves: wav[i] is the number of effective (useful waves) of individual i.
13829: Death is a valid wave (if date is known).
13830: mw[mi][i] is the number of (mi=1 to wav[i]) effective wave out of mi of individual i
13831: dh[m][i] or dh[mw[mi][i]][i] is the delay between two effective waves m=mw[mi][i]
13832: and mw[mi+1][i]. dh depends on stepm.
13833: */
13834:
1.126 brouard 13835: concatwav(wav, dh, bh, mw, s, agedc, agev, firstpass, lastpass, imx, nlstate, stepm);
1.248 brouard 13836: /* Concatenates waves */
1.145 brouard 13837:
1.290 brouard 13838: free_vector(moisdc,firstobs,lastobs);
13839: free_vector(andc,firstobs,lastobs);
1.215 brouard 13840:
1.126 brouard 13841: /* Routine tricode is to calculate cptcoveff (real number of unique covariates) and to associate covariable number and modality */
13842: nbcode=imatrix(0,NCOVMAX,0,NCOVMAX);
13843: ncodemax[1]=1;
1.145 brouard 13844: Ndum =ivector(-1,NCOVMAX);
1.225 brouard 13845: cptcoveff=0;
1.220 brouard 13846: if (ncovmodel-nagesqr > 2 ){ /* That is if covariate other than cst, age and age*age */
1.335 brouard 13847: tricode(&cptcoveff,Tvar,nbcode,imx, Ndum); /**< Fills nbcode[Tvar[j]][l]; as well as calculate cptcoveff or number of total effective dummy covariates*/
1.227 brouard 13848: }
13849:
13850: ncovcombmax=pow(2,cptcoveff);
1.338 brouard 13851: invalidvarcomb=ivector(0, ncovcombmax);
13852: for(i=0;i<ncovcombmax;i++)
1.227 brouard 13853: invalidvarcomb[i]=0;
13854:
1.211 brouard 13855: /* Nbcode gives the value of the lth modality (currently 1 to 2) of jth covariate, in
1.186 brouard 13856: V2+V1*age, there are 3 covariates Tvar[2]=1 (V1).*/
1.211 brouard 13857: /* 1 to ncodemax[j] which is the maximum value of this jth covariate */
1.227 brouard 13858:
1.200 brouard 13859: /* codtab=imatrix(1,100,1,10);*/ /* codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) */
1.198 brouard 13860: /*printf(" codtab[1,1],codtab[100,10]=%d,%d\n", codtab[1][1],codtabm(100,10));*/
1.186 brouard 13861: /* codtab gives the value 1 or 2 of the hth combination of k covariates (1 or 2).*/
1.211 brouard 13862: /* nbcode[Tvaraff[j]][codtabm(h,j)]) : if there are only 2 modalities for a covariate j,
13863: * codtabm(h,j) gives its value classified at position h and nbcode gives how it is coded
13864: * (currently 0 or 1) in the data.
13865: * In a loop on h=1 to 2**k, and a loop on j (=1 to k), we get the value of
13866: * corresponding modality (h,j).
13867: */
13868:
1.145 brouard 13869: h=0;
13870: /*if (cptcovn > 0) */
1.126 brouard 13871: m=pow(2,cptcoveff);
13872:
1.144 brouard 13873: /**< codtab(h,k) k = codtab[h,k]=( (h-1) - mod(k-1,2**(k-1) )/2**(k-1) + 1
1.211 brouard 13874: * For k=4 covariates, h goes from 1 to m=2**k
13875: * codtabm(h,k)= (1 & (h-1) >> (k-1)) + 1;
13876: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
1.329 brouard 13877: * h\k 1 2 3 4 * h-1\k-1 4 3 2 1
13878: *______________________________ *______________________
13879: * 1 i=1 1 i=1 1 i=1 1 i=1 1 * 0 0 0 0 0
13880: * 2 2 1 1 1 * 1 0 0 0 1
13881: * 3 i=2 1 2 1 1 * 2 0 0 1 0
13882: * 4 2 2 1 1 * 3 0 0 1 1
13883: * 5 i=3 1 i=2 1 2 1 * 4 0 1 0 0
13884: * 6 2 1 2 1 * 5 0 1 0 1
13885: * 7 i=4 1 2 2 1 * 6 0 1 1 0
13886: * 8 2 2 2 1 * 7 0 1 1 1
13887: * 9 i=5 1 i=3 1 i=2 1 2 * 8 1 0 0 0
13888: * 10 2 1 1 2 * 9 1 0 0 1
13889: * 11 i=6 1 2 1 2 * 10 1 0 1 0
13890: * 12 2 2 1 2 * 11 1 0 1 1
13891: * 13 i=7 1 i=4 1 2 2 * 12 1 1 0 0
13892: * 14 2 1 2 2 * 13 1 1 0 1
13893: * 15 i=8 1 2 2 2 * 14 1 1 1 0
13894: * 16 2 2 2 2 * 15 1 1 1 1
13895: */
1.212 brouard 13896: /* How to do the opposite? From combination h (=1 to 2**k) how to get the value on the covariates? */
1.211 brouard 13897: /* from h=5 and m, we get then number of covariates k=log(m)/log(2)=4
13898: * and the value of each covariate?
13899: * V1=1, V2=1, V3=2, V4=1 ?
13900: * h-1=4 and 4 is 0100 or reverse 0010, and +1 is 1121 ok.
13901: * h=6, 6-1=5, 5 is 0101, 1010, 2121, V1=2nd, V2=1st, V3=2nd, V4=1st.
13902: * In order to get the real value in the data, we use nbcode
13903: * nbcode[Tvar[3][2nd]]=1 and nbcode[Tvar[4][1]]=0
13904: * We are keeping this crazy system in order to be able (in the future?)
13905: * to have more than 2 values (0 or 1) for a covariate.
13906: * #define codtabm(h,k) (1 & (h-1) >> (k-1))+1
13907: * h=6, k=2? h-1=5=0101, reverse 1010, +1=2121, k=2nd position: value is 1: codtabm(6,2)=1
13908: * bbbbbbbb
13909: * 76543210
13910: * h-1 00000101 (6-1=5)
1.219 brouard 13911: *(h-1)>>(k-1)= 00000010 >> (2-1) = 1 right shift
1.211 brouard 13912: * &
13913: * 1 00000001 (1)
1.219 brouard 13914: * 00000000 = 1 & ((h-1) >> (k-1))
13915: * +1= 00000001 =1
1.211 brouard 13916: *
13917: * h=14, k=3 => h'=h-1=13, k'=k-1=2
13918: * h' 1101 =2^3+2^2+0x2^1+2^0
13919: * >>k' 11
13920: * & 00000001
13921: * = 00000001
13922: * +1 = 00000010=2 = codtabm(14,3)
13923: * Reverse h=6 and m=16?
13924: * cptcoveff=log(16)/log(2)=4 covariate: 6-1=5=0101 reversed=1010 +1=2121 =>V1=2, V2=1, V3=2, V4=1.
13925: * for (j=1 to cptcoveff) Vj=decodtabm(j,h,cptcoveff)
13926: * decodtabm(h,j,cptcoveff)= (((h-1) >> (j-1)) & 1) +1
13927: * decodtabm(h,j,cptcoveff)= (h <= (1<<cptcoveff)?(((h-1) >> (j-1)) & 1) +1 : -1)
13928: * V3=decodtabm(14,3,2**4)=2
13929: * h'=13 1101 =2^3+2^2+0x2^1+2^0
13930: *(h-1) >> (j-1) 0011 =13 >> 2
13931: * &1 000000001
13932: * = 000000001
13933: * +1= 000000010 =2
13934: * 2211
13935: * V1=1+1, V2=0+1, V3=1+1, V4=1+1
13936: * V3=2
1.220 brouard 13937: * codtabm and decodtabm are identical
1.211 brouard 13938: */
13939:
1.145 brouard 13940:
13941: free_ivector(Ndum,-1,NCOVMAX);
13942:
13943:
1.126 brouard 13944:
1.186 brouard 13945: /* Initialisation of ----------- gnuplot -------------*/
1.126 brouard 13946: strcpy(optionfilegnuplot,optionfilefiname);
13947: if(mle==-3)
1.201 brouard 13948: strcat(optionfilegnuplot,"-MORT_");
1.126 brouard 13949: strcat(optionfilegnuplot,".gp");
13950:
13951: if((ficgp=fopen(optionfilegnuplot,"w"))==NULL) {
13952: printf("Problem with file %s",optionfilegnuplot);
13953: }
13954: else{
1.204 brouard 13955: fprintf(ficgp,"\n# IMaCh-%s\n", version);
1.126 brouard 13956: fprintf(ficgp,"# %s\n", optionfilegnuplot);
1.141 brouard 13957: //fprintf(ficgp,"set missing 'NaNq'\n");
13958: fprintf(ficgp,"set datafile missing 'NaNq'\n");
1.126 brouard 13959: }
13960: /* fclose(ficgp);*/
1.186 brouard 13961:
13962:
13963: /* Initialisation of --------- index.htm --------*/
1.126 brouard 13964:
13965: strcpy(optionfilehtm,optionfilefiname); /* Main html file */
13966: if(mle==-3)
1.201 brouard 13967: strcat(optionfilehtm,"-MORT_");
1.126 brouard 13968: strcat(optionfilehtm,".htm");
13969: if((fichtm=fopen(optionfilehtm,"w"))==NULL) {
1.131 brouard 13970: printf("Problem with %s \n",optionfilehtm);
13971: exit(0);
1.126 brouard 13972: }
13973:
13974: strcpy(optionfilehtmcov,optionfilefiname); /* Only for matrix of covariance */
13975: strcat(optionfilehtmcov,"-cov.htm");
13976: if((fichtmcov=fopen(optionfilehtmcov,"w"))==NULL) {
13977: printf("Problem with %s \n",optionfilehtmcov), exit(0);
13978: }
13979: else{
13980: fprintf(fichtmcov,"<html><head>\n<title>IMaCh Cov %s</title></head>\n <body><font size=\"2\">%s <br> %s</font> \
13981: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13982: Title=%s <br>Datafile=%s Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n",\
1.126 brouard 13983: optionfilehtmcov,version,fullversion,title,datafile,firstpass,lastpass,stepm, weightopt, model);
13984: }
13985:
1.335 brouard 13986: fprintf(fichtm,"<html><head>\n<meta charset=\"utf-8\"/><meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\" />\n\
13987: <title>IMaCh %s</title></head>\n\
13988: <body><font size=\"7\"><a href=http:/euroreves.ined.fr/imach>IMaCh for Interpolated Markov Chain</a> </font><br>\n\
13989: <font size=\"3\">Sponsored by Copyright (C) 2002-2015 <a href=http://www.ined.fr>INED</a>\
13990: -EUROREVES-Institut de longévité-2013-2022-Japan Society for the Promotion of Sciences 日本学術振興会 \
13991: (<a href=https://www.jsps.go.jp/english/e-grants/>Grant-in-Aid for Scientific Research 25293121</a>) - \
13992: <a href=https://software.intel.com/en-us>Intel Software 2015-2018</a></font><br> \n", optionfilehtm);
13993:
13994: fprintf(fichtm,"<hr size=\"2\" color=\"#EC5E5E\"> \n\
1.204 brouard 13995: <font size=\"2\">IMaCh-%s <br> %s</font> \
1.126 brouard 13996: <hr size=\"2\" color=\"#EC5E5E\"> \n\
1.337 brouard 13997: This file: <a href=\"%s\">%s</a></br>Title=%s <br>Datafile=<a href=\"%s\">%s</a> Firstpass=%d Lastpass=%d Stepm=%d Weight=%d Model=1+age+%s<br>\n\
1.126 brouard 13998: \n\
13999: <hr size=\"2\" color=\"#EC5E5E\">\
14000: <ul><li><h4>Parameter files</h4>\n\
14001: - Parameter file: <a href=\"%s.%s\">%s.%s</a><br>\n\
14002: - Copy of the parameter file: <a href=\"o%s\">o%s</a><br>\n\
14003: - Log file of the run: <a href=\"%s\">%s</a><br>\n\
14004: - Gnuplot file name: <a href=\"%s\">%s</a><br>\n\
14005: - Date and time at start: %s</ul>\n",\
1.335 brouard 14006: version,fullversion,optionfilehtm,optionfilehtm,title,datafile,datafile,firstpass,lastpass,stepm, weightopt, model, \
1.126 brouard 14007: optionfilefiname,optionfilext,optionfilefiname,optionfilext,\
14008: fileres,fileres,\
14009: filelog,filelog,optionfilegnuplot,optionfilegnuplot,strstart);
14010: fflush(fichtm);
14011:
14012: strcpy(pathr,path);
14013: strcat(pathr,optionfilefiname);
1.184 brouard 14014: #ifdef WIN32
14015: _chdir(optionfilefiname); /* Move to directory named optionfile */
14016: #else
1.126 brouard 14017: chdir(optionfilefiname); /* Move to directory named optionfile */
1.184 brouard 14018: #endif
14019:
1.126 brouard 14020:
1.220 brouard 14021: /* Calculates basic frequencies. Computes observed prevalence at single age
14022: and for any valid combination of covariates
1.126 brouard 14023: and prints on file fileres'p'. */
1.251 brouard 14024: freqsummary(fileres, p, pstart, agemin, agemax, s, agev, nlstate, imx, Tvaraff, invalidvarcomb, nbcode, ncodemax,mint,anint,strstart, \
1.227 brouard 14025: firstpass, lastpass, stepm, weightopt, model);
1.126 brouard 14026:
14027: fprintf(fichtm,"\n");
1.286 brouard 14028: fprintf(fichtm,"<h4>Parameter line 2</h4><ul><li>Tolerance for the convergence of the likelihood: ftol=%g \n<li>Interval for the elementary matrix (in month): stepm=%d",\
1.274 brouard 14029: ftol, stepm);
14030: fprintf(fichtm,"\n<li>Number of fixed dummy covariates: ncovcol=%d ", ncovcol);
14031: ncurrv=1;
14032: for(i=ncurrv; i <=ncovcol; i++) fprintf(fichtm,"V%d ", i);
14033: fprintf(fichtm,"\n<li> Number of fixed quantitative variables: nqv=%d ", nqv);
14034: ncurrv=i;
14035: for(i=ncurrv; i <=ncurrv-1+nqv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 14036: fprintf(fichtm,"\n<li> Number of time varying (wave varying) dummy covariates: ntv=%d ", ntv);
1.274 brouard 14037: ncurrv=i;
14038: for(i=ncurrv; i <=ncurrv-1+ntv; i++) fprintf(fichtm,"V%d ", i);
1.290 brouard 14039: fprintf(fichtm,"\n<li>Number of time varying quantitative covariates: nqtv=%d ", nqtv);
1.274 brouard 14040: ncurrv=i;
14041: for(i=ncurrv; i <=ncurrv-1+nqtv; i++) fprintf(fichtm,"V%d ", i);
14042: fprintf(fichtm,"\n<li>Weights column \n<br>Number of alive states: nlstate=%d <br>Number of death states (not really implemented): ndeath=%d \n<li>Number of waves: maxwav=%d \n<li>Parameter for maximization (1), using parameter values (0), for design of parameters and variance-covariance matrix: mle=%d \n<li>Does the weight column be taken into account (1), or not (0): weight=%d</ul>\n", \
14043: nlstate, ndeath, maxwav, mle, weightopt);
14044:
14045: fprintf(fichtm,"<h4> Diagram of states <a href=\"%s_.svg\">%s_.svg</a></h4> \n\
14046: <img src=\"%s_.svg\">", subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"),subdirf2(optionfilefiname,"D_"));
14047:
14048:
1.317 brouard 14049: fprintf(fichtm,"\n<h4>Some descriptive statistics </h4>\n<br>Number of (used) observations=%d <br>\n\
1.126 brouard 14050: Youngest age at first (selected) pass %.2f, oldest age %.2f<br>\n\
14051: Interval (in months) between two waves: Min=%d Max=%d Mean=%.2lf<br>\n",\
1.274 brouard 14052: imx,agemin,agemax,jmin,jmax,jmean);
1.126 brouard 14053: pmmij= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
1.268 brouard 14054: oldms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14055: newms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14056: savms= matrix(1,nlstate+ndeath,1,nlstate+ndeath); /* creation */
14057: oldm=oldms; newm=newms; savm=savms; /* Keeps fixed addresses to free */
1.218 brouard 14058:
1.126 brouard 14059: /* For Powell, parameters are in a vector p[] starting at p[1]
14060: so we point p on param[1][1] so that p[1] maps on param[1][1][1] */
14061: p=param[1][1]; /* *(*(*(param +1)+1)+0) */
14062:
14063: globpr=0; /* To get the number ipmx of contributions and the sum of weights*/
1.186 brouard 14064: /* For mortality only */
1.126 brouard 14065: if (mle==-3){
1.136 brouard 14066: ximort=matrix(1,NDIM,1,NDIM);
1.248 brouard 14067: for(i=1;i<=NDIM;i++)
14068: for(j=1;j<=NDIM;j++)
14069: ximort[i][j]=0.;
1.186 brouard 14070: /* ximort=gsl_matrix_alloc(1,NDIM,1,NDIM); */
1.290 brouard 14071: cens=ivector(firstobs,lastobs);
14072: ageexmed=vector(firstobs,lastobs);
14073: agecens=vector(firstobs,lastobs);
14074: dcwave=ivector(firstobs,lastobs);
1.223 brouard 14075:
1.126 brouard 14076: for (i=1; i<=imx; i++){
14077: dcwave[i]=-1;
14078: for (m=firstpass; m<=lastpass; m++)
1.226 brouard 14079: if (s[m][i]>nlstate) {
14080: dcwave[i]=m;
14081: /* printf("i=%d j=%d s=%d dcwave=%d\n",i,j, s[j][i],dcwave[i]);*/
14082: break;
14083: }
1.126 brouard 14084: }
1.226 brouard 14085:
1.126 brouard 14086: for (i=1; i<=imx; i++) {
14087: if (wav[i]>0){
1.226 brouard 14088: ageexmed[i]=agev[mw[1][i]][i];
14089: j=wav[i];
14090: agecens[i]=1.;
14091:
14092: if (ageexmed[i]> 1 && wav[i] > 0){
14093: agecens[i]=agev[mw[j][i]][i];
14094: cens[i]= 1;
14095: }else if (ageexmed[i]< 1)
14096: cens[i]= -1;
14097: if (agedc[i]< AGESUP && agedc[i]>1 && dcwave[i]>firstpass && dcwave[i]<=lastpass)
14098: cens[i]=0 ;
1.126 brouard 14099: }
14100: else cens[i]=-1;
14101: }
14102:
14103: for (i=1;i<=NDIM;i++) {
14104: for (j=1;j<=NDIM;j++)
1.226 brouard 14105: ximort[i][j]=(i == j ? 1.0 : 0.0);
1.126 brouard 14106: }
14107:
1.302 brouard 14108: p[1]=0.0268; p[NDIM]=0.083;
14109: /* printf("%lf %lf", p[1], p[2]); */
1.126 brouard 14110:
14111:
1.136 brouard 14112: #ifdef GSL
14113: printf("GSL optimization\n"); fprintf(ficlog,"Powell\n");
1.162 brouard 14114: #else
1.126 brouard 14115: printf("Powell\n"); fprintf(ficlog,"Powell\n");
1.136 brouard 14116: #endif
1.201 brouard 14117: strcpy(filerespow,"POW-MORT_");
14118: strcat(filerespow,fileresu);
1.126 brouard 14119: if((ficrespow=fopen(filerespow,"w"))==NULL) {
14120: printf("Problem with resultfile: %s\n", filerespow);
14121: fprintf(ficlog,"Problem with resultfile: %s\n", filerespow);
14122: }
1.136 brouard 14123: #ifdef GSL
14124: fprintf(ficrespow,"# GSL optimization\n# iter -2*LL");
1.162 brouard 14125: #else
1.126 brouard 14126: fprintf(ficrespow,"# Powell\n# iter -2*LL");
1.136 brouard 14127: #endif
1.126 brouard 14128: /* for (i=1;i<=nlstate;i++)
14129: for(j=1;j<=nlstate+ndeath;j++)
14130: if(j!=i)fprintf(ficrespow," p%1d%1d",i,j);
14131: */
14132: fprintf(ficrespow,"\n");
1.136 brouard 14133: #ifdef GSL
14134: /* gsl starts here */
14135: T = gsl_multimin_fminimizer_nmsimplex;
14136: gsl_multimin_fminimizer *sfm = NULL;
14137: gsl_vector *ss, *x;
14138: gsl_multimin_function minex_func;
14139:
14140: /* Initial vertex size vector */
14141: ss = gsl_vector_alloc (NDIM);
14142:
14143: if (ss == NULL){
14144: GSL_ERROR_VAL ("failed to allocate space for ss", GSL_ENOMEM, 0);
14145: }
14146: /* Set all step sizes to 1 */
14147: gsl_vector_set_all (ss, 0.001);
14148:
14149: /* Starting point */
1.126 brouard 14150:
1.136 brouard 14151: x = gsl_vector_alloc (NDIM);
14152:
14153: if (x == NULL){
14154: gsl_vector_free(ss);
14155: GSL_ERROR_VAL ("failed to allocate space for x", GSL_ENOMEM, 0);
14156: }
14157:
14158: /* Initialize method and iterate */
14159: /* p[1]=0.0268; p[NDIM]=0.083; */
1.186 brouard 14160: /* gsl_vector_set(x, 0, 0.0268); */
14161: /* gsl_vector_set(x, 1, 0.083); */
1.136 brouard 14162: gsl_vector_set(x, 0, p[1]);
14163: gsl_vector_set(x, 1, p[2]);
14164:
14165: minex_func.f = &gompertz_f;
14166: minex_func.n = NDIM;
14167: minex_func.params = (void *)&p; /* ??? */
14168:
14169: sfm = gsl_multimin_fminimizer_alloc (T, NDIM);
14170: gsl_multimin_fminimizer_set (sfm, &minex_func, x, ss);
14171:
14172: printf("Iterations beginning .....\n\n");
14173: printf("Iter. # Intercept Slope -Log Likelihood Simplex size\n");
14174:
14175: iteri=0;
14176: while (rval == GSL_CONTINUE){
14177: iteri++;
14178: status = gsl_multimin_fminimizer_iterate(sfm);
14179:
14180: if (status) printf("error: %s\n", gsl_strerror (status));
14181: fflush(0);
14182:
14183: if (status)
14184: break;
14185:
14186: rval = gsl_multimin_test_size (gsl_multimin_fminimizer_size (sfm), 1e-6);
14187: ssval = gsl_multimin_fminimizer_size (sfm);
14188:
14189: if (rval == GSL_SUCCESS)
14190: printf ("converged to a local maximum at\n");
14191:
14192: printf("%5d ", iteri);
14193: for (it = 0; it < NDIM; it++){
14194: printf ("%10.5f ", gsl_vector_get (sfm->x, it));
14195: }
14196: printf("f() = %-10.5f ssize = %.7f\n", sfm->fval, ssval);
14197: }
14198:
14199: printf("\n\n Please note: Program should be run many times with varying starting points to detemine global maximum\n\n");
14200:
14201: gsl_vector_free(x); /* initial values */
14202: gsl_vector_free(ss); /* inital step size */
14203: for (it=0; it<NDIM; it++){
14204: p[it+1]=gsl_vector_get(sfm->x,it);
14205: fprintf(ficrespow," %.12lf", p[it]);
14206: }
14207: gsl_multimin_fminimizer_free (sfm); /* p *(sfm.x.data) et p *(sfm.x.data+1) */
14208: #endif
14209: #ifdef POWELL
14210: powell(p,ximort,NDIM,ftol,&iter,&fret,gompertz);
14211: #endif
1.126 brouard 14212: fclose(ficrespow);
14213:
1.203 brouard 14214: hesscov(matcov, hess, p, NDIM, delti, 1e-4, gompertz);
1.126 brouard 14215:
14216: for(i=1; i <=NDIM; i++)
14217: for(j=i+1;j<=NDIM;j++)
1.220 brouard 14218: matcov[i][j]=matcov[j][i];
1.126 brouard 14219:
14220: printf("\nCovariance matrix\n ");
1.203 brouard 14221: fprintf(ficlog,"\nCovariance matrix\n ");
1.126 brouard 14222: for(i=1; i <=NDIM; i++) {
14223: for(j=1;j<=NDIM;j++){
1.220 brouard 14224: printf("%f ",matcov[i][j]);
14225: fprintf(ficlog,"%f ",matcov[i][j]);
1.126 brouard 14226: }
1.203 brouard 14227: printf("\n "); fprintf(ficlog,"\n ");
1.126 brouard 14228: }
14229:
14230: printf("iter=%d MLE=%f Eq=%lf*exp(%lf*(age-%d))\n",iter,-gompertz(p),p[1],p[2],agegomp);
1.193 brouard 14231: for (i=1;i<=NDIM;i++) {
1.126 brouard 14232: printf("%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
1.193 brouard 14233: fprintf(ficlog,"%f [%f ; %f]\n",p[i],p[i]-2*sqrt(matcov[i][i]),p[i]+2*sqrt(matcov[i][i]));
14234: }
1.302 brouard 14235: lsurv=vector(agegomp,AGESUP);
14236: lpop=vector(agegomp,AGESUP);
14237: tpop=vector(agegomp,AGESUP);
1.126 brouard 14238: lsurv[agegomp]=100000;
14239:
14240: for (k=agegomp;k<=AGESUP;k++) {
14241: agemortsup=k;
14242: if (p[1]*exp(p[2]*(k-agegomp))>1) break;
14243: }
14244:
14245: for (k=agegomp;k<agemortsup;k++)
14246: lsurv[k+1]=lsurv[k]-lsurv[k]*(p[1]*exp(p[2]*(k-agegomp)));
14247:
14248: for (k=agegomp;k<agemortsup;k++){
14249: lpop[k]=(lsurv[k]+lsurv[k+1])/2.;
14250: sumlpop=sumlpop+lpop[k];
14251: }
14252:
14253: tpop[agegomp]=sumlpop;
14254: for (k=agegomp;k<(agemortsup-3);k++){
14255: /* tpop[k+1]=2;*/
14256: tpop[k+1]=tpop[k]-lpop[k];
14257: }
14258:
14259:
14260: printf("\nAge lx qx dx Lx Tx e(x)\n");
14261: for (k=agegomp;k<(agemortsup-2);k++)
14262: printf("%d %.0lf %lf %.0lf %.0lf %.0lf %lf\n",k,lsurv[k],p[1]*exp(p[2]*(k-agegomp)),(p[1]*exp(p[2]*(k-agegomp)))*lsurv[k],lpop[k],tpop[k],tpop[k]/lsurv[k]);
14263:
14264:
14265: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.220 brouard 14266: ageminpar=50;
14267: agemaxpar=100;
1.194 brouard 14268: if(ageminpar == AGEOVERFLOW ||agemaxpar == AGEOVERFLOW){
14269: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14270: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14271: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
14272: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
14273: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14274: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14275: }else{
14276: printf("Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
14277: fprintf(ficlog,"Warning! ageminpar %f and agemaxpar %f have been fixed because for simplification until it is fixed...\n\n",ageminpar,agemaxpar);
1.201 brouard 14278: printinggnuplotmort(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, pathc,p);
1.220 brouard 14279: }
1.201 brouard 14280: printinghtmlmort(fileresu,title,datafile, firstpass, lastpass, \
1.126 brouard 14281: stepm, weightopt,\
14282: model,imx,p,matcov,agemortsup);
14283:
1.302 brouard 14284: free_vector(lsurv,agegomp,AGESUP);
14285: free_vector(lpop,agegomp,AGESUP);
14286: free_vector(tpop,agegomp,AGESUP);
1.220 brouard 14287: free_matrix(ximort,1,NDIM,1,NDIM);
1.290 brouard 14288: free_ivector(dcwave,firstobs,lastobs);
14289: free_vector(agecens,firstobs,lastobs);
14290: free_vector(ageexmed,firstobs,lastobs);
14291: free_ivector(cens,firstobs,lastobs);
1.220 brouard 14292: #ifdef GSL
1.136 brouard 14293: #endif
1.186 brouard 14294: } /* Endof if mle==-3 mortality only */
1.205 brouard 14295: /* Standard */
14296: else{ /* For mle !=- 3, could be 0 or 1 or 4 etc. */
14297: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14298: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
1.132 brouard 14299: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
1.126 brouard 14300: printf("First Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
14301: for (k=1; k<=npar;k++)
14302: printf(" %d %8.5f",k,p[k]);
14303: printf("\n");
1.205 brouard 14304: if(mle>=1){ /* Could be 1 or 2, Real Maximization */
14305: /* mlikeli uses func not funcone */
1.247 brouard 14306: /* for(i=1;i<nlstate;i++){ */
14307: /* /\*reducing xi for 1 to npar to 1 to ncovmodel; *\/ */
14308: /* mlikeli(ficres,p, ncovmodel, ncovmodel, nlstate, ftol, funcnoprod); */
14309: /* } */
1.205 brouard 14310: mlikeli(ficres,p, npar, ncovmodel, nlstate, ftol, func);
14311: }
14312: if(mle==0) {/* No optimization, will print the likelihoods for the datafile */
14313: globpr=0;/* Computes sum of likelihood for globpr=1 and funcone */
14314: /* Computes likelihood for initial parameters, uses funcone to compute gpimx and gsw */
14315: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14316: }
14317: globpr=1; /* again, to print the individual contributions using computed gpimx and gsw */
1.126 brouard 14318: likelione(ficres, p, npar, nlstate, &globpr, &ipmx, &sw, &fretone, funcone); /* Prints the contributions to the likelihood */
14319: printf("Second Likeli=%12.6f ipmx=%ld sw=%12.6f",fretone,ipmx,sw);
1.335 brouard 14320: /* exit(0); */
1.126 brouard 14321: for (k=1; k<=npar;k++)
14322: printf(" %d %8.5f",k,p[k]);
14323: printf("\n");
14324:
14325: /*--------- results files --------------*/
1.283 brouard 14326: /* fprintf(ficres,"title=%s datafile=%s lastobs=%d firstpass=%d lastpass=%d\nftol=%e stepm=%d ncovcol=%d nqv=%d ntv=%d nqtv=%d nlstate=%d ndeath=%d maxwav=%d mle= 0 weight=%d\nmodel=1+age+%s.\n", title, datafile, lastobs, firstpass,lastpass,ftol, stepm, ncovcol, nqv, ntv, nqtv, nlstate, ndeath, maxwav, weightopt,model); */
1.126 brouard 14327:
14328:
14329: fprintf(ficres,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14330: printf("# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n"); /* Printing model equation */
1.126 brouard 14331: fprintf(ficlog,"# Parameters nlstate*nlstate*ncov a12*1 + b12 * age + ...\n");
1.319 brouard 14332:
14333: printf("#model= 1 + age ");
14334: fprintf(ficres,"#model= 1 + age ");
14335: fprintf(ficlog,"#model= 1 + age ");
14336: fprintf(fichtm,"\n<ul><li> model=1+age+%s\n \
14337: </ul>", model);
14338:
14339: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">\n");
14340: fprintf(fichtm, "<tr><th>Model=</th><th>1</th><th>+ age</th>");
14341: if(nagesqr==1){
14342: printf(" + age*age ");
14343: fprintf(ficres," + age*age ");
14344: fprintf(ficlog," + age*age ");
14345: fprintf(fichtm, "<th>+ age*age</th>");
14346: }
14347: for(j=1;j <=ncovmodel-2;j++){
14348: if(Typevar[j]==0) {
14349: printf(" + V%d ",Tvar[j]);
14350: fprintf(ficres," + V%d ",Tvar[j]);
14351: fprintf(ficlog," + V%d ",Tvar[j]);
14352: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14353: }else if(Typevar[j]==1) {
14354: printf(" + V%d*age ",Tvar[j]);
14355: fprintf(ficres," + V%d*age ",Tvar[j]);
14356: fprintf(ficlog," + V%d*age ",Tvar[j]);
14357: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14358: }else if(Typevar[j]==2) {
14359: printf(" + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14360: fprintf(ficres," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14361: fprintf(ficlog," + V%d*V%d ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14362: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14363: }else if(Typevar[j]==3) { /* TO VERIFY */
14364: printf(" + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14365: fprintf(ficres," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14366: fprintf(ficlog," + V%d*V%d*age ",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
14367: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14368: }
14369: }
14370: printf("\n");
14371: fprintf(ficres,"\n");
14372: fprintf(ficlog,"\n");
14373: fprintf(fichtm, "</tr>");
14374: fprintf(fichtm, "\n");
14375:
14376:
1.126 brouard 14377: for(i=1,jk=1; i <=nlstate; i++){
14378: for(k=1; k <=(nlstate+ndeath); k++){
1.225 brouard 14379: if (k != i) {
1.319 brouard 14380: fprintf(fichtm, "<tr>");
1.225 brouard 14381: printf("%d%d ",i,k);
14382: fprintf(ficlog,"%d%d ",i,k);
14383: fprintf(ficres,"%1d%1d ",i,k);
1.319 brouard 14384: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14385: for(j=1; j <=ncovmodel; j++){
14386: printf("%12.7f ",p[jk]);
14387: fprintf(ficlog,"%12.7f ",p[jk]);
14388: fprintf(ficres,"%12.7f ",p[jk]);
1.319 brouard 14389: fprintf(fichtm, "<td>%12.7f</td>",p[jk]);
1.225 brouard 14390: jk++;
14391: }
14392: printf("\n");
14393: fprintf(ficlog,"\n");
14394: fprintf(ficres,"\n");
1.319 brouard 14395: fprintf(fichtm, "</tr>\n");
1.225 brouard 14396: }
1.126 brouard 14397: }
14398: }
1.319 brouard 14399: /* fprintf(fichtm,"</tr>\n"); */
14400: fprintf(fichtm,"</table>\n");
14401: fprintf(fichtm, "\n");
14402:
1.203 brouard 14403: if(mle != 0){
14404: /* Computing hessian and covariance matrix only at a peak of the Likelihood, that is after optimization */
1.126 brouard 14405: ftolhess=ftol; /* Usually correct */
1.203 brouard 14406: hesscov(matcov, hess, p, npar, delti, ftolhess, func);
14407: printf("Parameters and 95%% confidence intervals\n W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n And Wald-based confidence intervals plus and minus 1.96 * W .\n But be careful that parameters are highly correlated because incidence of disability is highly correlated to incidence of recovery.\n It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n");
14408: fprintf(ficlog, "Parameters, Wald tests and Wald-based confidence intervals\n W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n And Wald-based confidence intervals plus and minus 1.96 * W \n It might be better to visualize the covariance matrix. See the page 'Matrix of variance-covariance of one-step probabilities' and its graphs.\n");
1.322 brouard 14409: fprintf(fichtm, "\n<p>The Wald test results are output only if the maximimzation of the Likelihood is performed (mle=1)\n</br>Parameters, Wald tests and Wald-based confidence intervals\n</br> W is simply the result of the division of the parameter by the square root of covariance of the parameter.\n</br> And Wald-based confidence intervals plus and minus 1.96 * W \n </br> It might be better to visualize the covariance matrix. See the page '<a href=\"%s\">Matrix of variance-covariance of one-step probabilities and its graphs</a>'.\n</br>",optionfilehtmcov);
1.319 brouard 14410: fprintf(fichtm,"\n<table style=\"text-align:center; border: 1px solid\">");
14411: fprintf(fichtm, "\n<tr><th>Model=</th><th>1</th><th>+ age</th>");
14412: if(nagesqr==1){
14413: printf(" + age*age ");
14414: fprintf(ficres," + age*age ");
14415: fprintf(ficlog," + age*age ");
14416: fprintf(fichtm, "<th>+ age*age</th>");
14417: }
14418: for(j=1;j <=ncovmodel-2;j++){
14419: if(Typevar[j]==0) {
14420: printf(" + V%d ",Tvar[j]);
14421: fprintf(fichtm, "<th>+ V%d</th>",Tvar[j]);
14422: }else if(Typevar[j]==1) {
14423: printf(" + V%d*age ",Tvar[j]);
14424: fprintf(fichtm, "<th>+ V%d*age</th>",Tvar[j]);
14425: }else if(Typevar[j]==2) {
14426: fprintf(fichtm, "<th>+ V%d*V%d</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.349 brouard 14427: }else if(Typevar[j]==3) { /* TO VERIFY */
14428: fprintf(fichtm, "<th>+ V%d*V%d*age</th>",Tvard[Tposprod[j]][1],Tvard[Tposprod[j]][2]);
1.319 brouard 14429: }
14430: }
14431: fprintf(fichtm, "</tr>\n");
14432:
1.203 brouard 14433: for(i=1,jk=1; i <=nlstate; i++){
1.225 brouard 14434: for(k=1; k <=(nlstate+ndeath); k++){
14435: if (k != i) {
1.319 brouard 14436: fprintf(fichtm, "<tr valign=top>");
1.225 brouard 14437: printf("%d%d ",i,k);
14438: fprintf(ficlog,"%d%d ",i,k);
1.319 brouard 14439: fprintf(fichtm, "<td>%1d%1d</td>",i,k);
1.225 brouard 14440: for(j=1; j <=ncovmodel; j++){
1.319 brouard 14441: wald=p[jk]/sqrt(matcov[jk][jk]);
1.324 brouard 14442: printf("%12.7f(%12.7f) W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
14443: fprintf(ficlog,"%12.7f(%12.7f) W=%8.3f CI=[%12.7f ; %12.7f] ",p[jk],sqrt(matcov[jk][jk]), p[jk]/sqrt(matcov[jk][jk]), p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
1.319 brouard 14444: if(fabs(wald) > 1.96){
1.321 brouard 14445: fprintf(fichtm, "<td><b>%12.7f</b></br> (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
1.319 brouard 14446: }else{
14447: fprintf(fichtm, "<td>%12.7f (%12.7f)</br>",p[jk],sqrt(matcov[jk][jk]));
14448: }
1.324 brouard 14449: fprintf(fichtm,"W=%8.3f</br>",wald);
1.319 brouard 14450: fprintf(fichtm,"[%12.7f;%12.7f]</br></td>", p[jk]-1.96*sqrt(matcov[jk][jk]),p[jk]+1.96*sqrt(matcov[jk][jk]));
1.225 brouard 14451: jk++;
14452: }
14453: printf("\n");
14454: fprintf(ficlog,"\n");
1.319 brouard 14455: fprintf(fichtm, "</tr>\n");
1.225 brouard 14456: }
14457: }
1.193 brouard 14458: }
1.203 brouard 14459: } /* end of hesscov and Wald tests */
1.319 brouard 14460: fprintf(fichtm,"</table>\n");
1.225 brouard 14461:
1.203 brouard 14462: /* */
1.126 brouard 14463: fprintf(ficres,"# Scales (for hessian or gradient estimation)\n");
14464: printf("# Scales (for hessian or gradient estimation)\n");
14465: fprintf(ficlog,"# Scales (for hessian or gradient estimation)\n");
14466: for(i=1,jk=1; i <=nlstate; i++){
14467: for(j=1; j <=nlstate+ndeath; j++){
1.225 brouard 14468: if (j!=i) {
14469: fprintf(ficres,"%1d%1d",i,j);
14470: printf("%1d%1d",i,j);
14471: fprintf(ficlog,"%1d%1d",i,j);
14472: for(k=1; k<=ncovmodel;k++){
14473: printf(" %.5e",delti[jk]);
14474: fprintf(ficlog," %.5e",delti[jk]);
14475: fprintf(ficres," %.5e",delti[jk]);
14476: jk++;
14477: }
14478: printf("\n");
14479: fprintf(ficlog,"\n");
14480: fprintf(ficres,"\n");
14481: }
1.126 brouard 14482: }
14483: }
14484:
14485: fprintf(ficres,"# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n");
1.349 brouard 14486: if(mle >= 1) /* Too big for the screen */
1.126 brouard 14487: printf("# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n");
14488: fprintf(ficlog,"# Covariance matrix \n# 121 Var(a12)\n# 122 Cov(b12,a12) Var(b12)\n# ...\n# 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n");
14489: /* # 121 Var(a12)\n\ */
14490: /* # 122 Cov(b12,a12) Var(b12)\n\ */
14491: /* # 131 Cov(a13,a12) Cov(a13,b12, Var(a13)\n\ */
14492: /* # 132 Cov(b13,a12) Cov(b13,b12, Cov(b13,a13) Var(b13)\n\ */
14493: /* # 212 Cov(a21,a12) Cov(a21,b12, Cov(a21,a13) Cov(a21,b13) Var(a21)\n\ */
14494: /* # 212 Cov(b21,a12) Cov(b21,b12, Cov(b21,a13) Cov(b21,b13) Cov(b21,a21) Var(b21)\n\ */
14495: /* # 232 Cov(a23,a12) Cov(a23,b12, Cov(a23,a13) Cov(a23,b13) Cov(a23,a21) Cov(a23,b21) Var(a23)\n\ */
14496: /* # 232 Cov(b23,a12) Cov(b23,b12) ... Var (b23)\n" */
14497:
14498:
14499: /* Just to have a covariance matrix which will be more understandable
14500: even is we still don't want to manage dictionary of variables
14501: */
14502: for(itimes=1;itimes<=2;itimes++){
14503: jj=0;
14504: for(i=1; i <=nlstate; i++){
1.225 brouard 14505: for(j=1; j <=nlstate+ndeath; j++){
14506: if(j==i) continue;
14507: for(k=1; k<=ncovmodel;k++){
14508: jj++;
14509: ca[0]= k+'a'-1;ca[1]='\0';
14510: if(itimes==1){
14511: if(mle>=1)
14512: printf("#%1d%1d%d",i,j,k);
14513: fprintf(ficlog,"#%1d%1d%d",i,j,k);
14514: fprintf(ficres,"#%1d%1d%d",i,j,k);
14515: }else{
14516: if(mle>=1)
14517: printf("%1d%1d%d",i,j,k);
14518: fprintf(ficlog,"%1d%1d%d",i,j,k);
14519: fprintf(ficres,"%1d%1d%d",i,j,k);
14520: }
14521: ll=0;
14522: for(li=1;li <=nlstate; li++){
14523: for(lj=1;lj <=nlstate+ndeath; lj++){
14524: if(lj==li) continue;
14525: for(lk=1;lk<=ncovmodel;lk++){
14526: ll++;
14527: if(ll<=jj){
14528: cb[0]= lk +'a'-1;cb[1]='\0';
14529: if(ll<jj){
14530: if(itimes==1){
14531: if(mle>=1)
14532: printf(" Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14533: fprintf(ficlog," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14534: fprintf(ficres," Cov(%s%1d%1d,%s%1d%1d)",ca,i,j,cb, li,lj);
14535: }else{
14536: if(mle>=1)
14537: printf(" %.5e",matcov[jj][ll]);
14538: fprintf(ficlog," %.5e",matcov[jj][ll]);
14539: fprintf(ficres," %.5e",matcov[jj][ll]);
14540: }
14541: }else{
14542: if(itimes==1){
14543: if(mle>=1)
14544: printf(" Var(%s%1d%1d)",ca,i,j);
14545: fprintf(ficlog," Var(%s%1d%1d)",ca,i,j);
14546: fprintf(ficres," Var(%s%1d%1d)",ca,i,j);
14547: }else{
14548: if(mle>=1)
14549: printf(" %.7e",matcov[jj][ll]);
14550: fprintf(ficlog," %.7e",matcov[jj][ll]);
14551: fprintf(ficres," %.7e",matcov[jj][ll]);
14552: }
14553: }
14554: }
14555: } /* end lk */
14556: } /* end lj */
14557: } /* end li */
14558: if(mle>=1)
14559: printf("\n");
14560: fprintf(ficlog,"\n");
14561: fprintf(ficres,"\n");
14562: numlinepar++;
14563: } /* end k*/
14564: } /*end j */
1.126 brouard 14565: } /* end i */
14566: } /* end itimes */
14567:
14568: fflush(ficlog);
14569: fflush(ficres);
1.225 brouard 14570: while(fgets(line, MAXLINE, ficpar)) {
14571: /* If line starts with a # it is a comment */
14572: if (line[0] == '#') {
14573: numlinepar++;
14574: fputs(line,stdout);
14575: fputs(line,ficparo);
14576: fputs(line,ficlog);
1.299 brouard 14577: fputs(line,ficres);
1.225 brouard 14578: continue;
14579: }else
14580: break;
14581: }
14582:
1.209 brouard 14583: /* while((c=getc(ficpar))=='#' && c!= EOF){ */
14584: /* ungetc(c,ficpar); */
14585: /* fgets(line, MAXLINE, ficpar); */
14586: /* fputs(line,stdout); */
14587: /* fputs(line,ficparo); */
14588: /* } */
14589: /* ungetc(c,ficpar); */
1.126 brouard 14590:
14591: estepm=0;
1.209 brouard 14592: if((num_filled=sscanf(line,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm, &ftolpl)) !=EOF){
1.225 brouard 14593:
14594: if (num_filled != 6) {
14595: printf("Error: Not 6 parameters in line, for example:agemin=60 agemax=95 bage=55 fage=95 estepm=24 ftolpl=6e-4\n, your line=%s . Probably you are running an older format.\n",line);
14596: fprintf(ficlog,"Error: Not 6 parameters in line, for example:agemin=60 agemax=95 bage=55 fage=95 estepm=24 ftolpl=6e-4\n, your line=%s . Probably you are running an older format.\n",line);
14597: goto end;
14598: }
14599: printf("agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%lf\n",ageminpar,agemaxpar, bage, fage, estepm, ftolpl);
14600: }
14601: /* ftolpl=6*ftol*1.e5; /\* 6.e-3 make convergences in less than 80 loops for the prevalence limit *\/ */
14602: /*ftolpl=6.e-4;*/ /* 6.e-3 make convergences in less than 80 loops for the prevalence limit */
14603:
1.209 brouard 14604: /* fscanf(ficpar,"agemin=%lf agemax=%lf bage=%lf fage=%lf estepm=%d ftolpl=%\n",&ageminpar,&agemaxpar, &bage, &fage, &estepm); */
1.126 brouard 14605: if (estepm==0 || estepm < stepm) estepm=stepm;
14606: if (fage <= 2) {
14607: bage = ageminpar;
14608: fage = agemaxpar;
14609: }
14610:
14611: fprintf(ficres,"# agemin agemax for life expectancy, bage fage (if mle==0 ie no data nor Max likelihood).\n");
1.211 brouard 14612: fprintf(ficres,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
14613: fprintf(ficparo,"agemin=%.0f agemax=%.0f bage=%.0f fage=%.0f estepm=%d, ftolpl=%e\n",ageminpar,agemaxpar,bage,fage, estepm, ftolpl);
1.220 brouard 14614:
1.186 brouard 14615: /* Other stuffs, more or less useful */
1.254 brouard 14616: while(fgets(line, MAXLINE, ficpar)) {
14617: /* If line starts with a # it is a comment */
14618: if (line[0] == '#') {
14619: numlinepar++;
14620: fputs(line,stdout);
14621: fputs(line,ficparo);
14622: fputs(line,ficlog);
1.299 brouard 14623: fputs(line,ficres);
1.254 brouard 14624: continue;
14625: }else
14626: break;
14627: }
14628:
14629: if((num_filled=sscanf(line,"begin-prev-date=%lf/%lf/%lf end-prev-date=%lf/%lf/%lf mov_average=%d\n",&jprev1, &mprev1,&anprev1,&jprev2, &mprev2,&anprev2,&mobilav)) !=EOF){
14630:
14631: if (num_filled != 7) {
14632: printf("Error: Not 7 (data)parameters in line but %d, for example:begin-prev-date=1/1/1990 end-prev-date=1/6/2004 mov_average=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
14633: fprintf(ficlog,"Error: Not 7 (data)parameters in line but %d, for example:begin-prev-date=1/1/1990 end-prev-date=1/6/2004 mov_average=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
14634: goto end;
14635: }
14636: printf("begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
14637: fprintf(ficparo,"begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
14638: fprintf(ficres,"begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
14639: fprintf(ficlog,"begin-prev-date=%.lf/%.lf/%.lf end-prev-date=%.lf/%.lf/%.lf mov_average=%d\n",jprev1, mprev1,anprev1,jprev2, mprev2,anprev2,mobilav);
1.126 brouard 14640: }
1.254 brouard 14641:
14642: while(fgets(line, MAXLINE, ficpar)) {
14643: /* If line starts with a # it is a comment */
14644: if (line[0] == '#') {
14645: numlinepar++;
14646: fputs(line,stdout);
14647: fputs(line,ficparo);
14648: fputs(line,ficlog);
1.299 brouard 14649: fputs(line,ficres);
1.254 brouard 14650: continue;
14651: }else
14652: break;
1.126 brouard 14653: }
14654:
14655:
14656: dateprev1=anprev1+(mprev1-1)/12.+(jprev1-1)/365.;
14657: dateprev2=anprev2+(mprev2-1)/12.+(jprev2-1)/365.;
14658:
1.254 brouard 14659: if((num_filled=sscanf(line,"pop_based=%d\n",&popbased)) !=EOF){
14660: if (num_filled != 1) {
14661: printf("Error: Not 1 (data)parameters in line but %d, for example:pop_based=0\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
14662: fprintf(ficlog,"Error: Not 1 (data)parameters in line but %d, for example: pop_based=1\n, your line=%s . Probably you are running an older format.\n",num_filled,line);
14663: goto end;
14664: }
14665: printf("pop_based=%d\n",popbased);
14666: fprintf(ficlog,"pop_based=%d\n",popbased);
14667: fprintf(ficparo,"pop_based=%d\n",popbased);
14668: fprintf(ficres,"pop_based=%d\n",popbased);
14669: }
14670:
1.258 brouard 14671: /* Results */
1.332 brouard 14672: /* Value of covariate in each resultine will be compututed (if product) and sorted according to model rank */
14673: /* It is precov[] because we need the varying age in order to compute the real cov[] of the model equation */
14674: precov=matrix(1,MAXRESULTLINESPONE,1,NCOVMAX+1);
1.307 brouard 14675: endishere=0;
1.258 brouard 14676: nresult=0;
1.308 brouard 14677: parameterline=0;
1.258 brouard 14678: do{
14679: if(!fgets(line, MAXLINE, ficpar)){
14680: endishere=1;
1.308 brouard 14681: parameterline=15;
1.258 brouard 14682: }else if (line[0] == '#') {
14683: /* If line starts with a # it is a comment */
1.254 brouard 14684: numlinepar++;
14685: fputs(line,stdout);
14686: fputs(line,ficparo);
14687: fputs(line,ficlog);
1.299 brouard 14688: fputs(line,ficres);
1.254 brouard 14689: continue;
1.258 brouard 14690: }else if(sscanf(line,"prevforecast=%[^\n]\n",modeltemp))
14691: parameterline=11;
1.296 brouard 14692: else if(sscanf(line,"prevbackcast=%[^\n]\n",modeltemp))
1.258 brouard 14693: parameterline=12;
1.307 brouard 14694: else if(sscanf(line,"result:%[^\n]\n",modeltemp)){
1.258 brouard 14695: parameterline=13;
1.307 brouard 14696: }
1.258 brouard 14697: else{
14698: parameterline=14;
1.254 brouard 14699: }
1.308 brouard 14700: switch (parameterline){ /* =0 only if only comments */
1.258 brouard 14701: case 11:
1.296 brouard 14702: if((num_filled=sscanf(line,"prevforecast=%d starting-proj-date=%lf/%lf/%lf final-proj-date=%lf/%lf/%lf mobil_average=%d\n",&prevfcast,&jproj1,&mproj1,&anproj1,&jproj2,&mproj2,&anproj2,&mobilavproj)) !=EOF && (num_filled == 8)){
14703: fprintf(ficparo,"prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj);
1.258 brouard 14704: printf("prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj);
14705: fprintf(ficlog,"prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj);
14706: fprintf(ficres,"prevforecast=%d starting-proj-date=%.lf/%.lf/%.lf final-proj-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevfcast,jproj1,mproj1,anproj1,jproj2,mproj2,anproj2,mobilavproj);
14707: /* day and month of proj2 are not used but only year anproj2.*/
1.273 brouard 14708: dateproj1=anproj1+(mproj1-1)/12.+(jproj1-1)/365.;
14709: dateproj2=anproj2+(mproj2-1)/12.+(jproj2-1)/365.;
1.296 brouard 14710: prvforecast = 1;
14711: }
14712: else if((num_filled=sscanf(line,"prevforecast=%d yearsfproj=%lf mobil_average=%d\n",&prevfcast,&yrfproj,&mobilavproj)) !=EOF){/* && (num_filled == 3))*/
1.313 brouard 14713: printf("prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14714: fprintf(ficlog,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
14715: fprintf(ficres,"prevforecast=%d yearsfproj=%.2lf mobil_average=%d\n",prevfcast,yrfproj,mobilavproj);
1.296 brouard 14716: prvforecast = 2;
14717: }
14718: else {
14719: printf("Error: Not 8 (data)parameters in line but %d, for example:prevforecast=1 starting-proj-date=1/1/1990 final-proj-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevforecast=1 yearsfproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
14720: fprintf(ficlog,"Error: Not 8 (data)parameters in line but %d, for example:prevforecast=1 starting-proj-date=1/1/1990 final-proj-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevforecast=1 yearproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
14721: goto end;
1.258 brouard 14722: }
1.254 brouard 14723: break;
1.258 brouard 14724: case 12:
1.296 brouard 14725: if((num_filled=sscanf(line,"prevbackcast=%d starting-back-date=%lf/%lf/%lf final-back-date=%lf/%lf/%lf mobil_average=%d\n",&prevbcast,&jback1,&mback1,&anback1,&jback2,&mback2,&anback2,&mobilavproj)) !=EOF && (num_filled == 8)){
14726: fprintf(ficparo,"prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
14727: printf("prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
14728: fprintf(ficlog,"prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
14729: fprintf(ficres,"prevbackcast=%d starting-back-date=%.lf/%.lf/%.lf final-back-date=%.lf/%.lf/%.lf mobil_average=%d\n",prevbcast,jback1,mback1,anback1,jback2,mback2,anback2,mobilavproj);
14730: /* day and month of back2 are not used but only year anback2.*/
1.273 brouard 14731: dateback1=anback1+(mback1-1)/12.+(jback1-1)/365.;
14732: dateback2=anback2+(mback2-1)/12.+(jback2-1)/365.;
1.296 brouard 14733: prvbackcast = 1;
14734: }
14735: else if((num_filled=sscanf(line,"prevbackcast=%d yearsbproj=%lf mobil_average=%d\n",&prevbcast,&yrbproj,&mobilavproj)) ==3){/* && (num_filled == 3))*/
1.313 brouard 14736: printf("prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14737: fprintf(ficlog,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
14738: fprintf(ficres,"prevbackcast=%d yearsbproj=%.2lf mobil_average=%d\n",prevbcast,yrbproj,mobilavproj);
1.296 brouard 14739: prvbackcast = 2;
14740: }
14741: else {
14742: printf("Error: Not 8 (data)parameters in line but %d, for example:prevbackcast=1 starting-back-date=1/1/1990 final-back-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevbackcast=1 yearsbproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
14743: fprintf(ficlog,"Error: Not 8 (data)parameters in line but %d, for example:prevbackcast=1 starting-back-date=1/1/1990 final-back-date=1/1/2000 mobil_average=0\nnor 3 (data)parameters, for example:prevbackcast=1 yearbproj=10 mobil_average=0. Your line=%s . You are running probably an older format.\n, ",num_filled,line);
14744: goto end;
1.258 brouard 14745: }
1.230 brouard 14746: break;
1.258 brouard 14747: case 13:
1.332 brouard 14748: num_filled=sscanf(line,"result:%[^\n]\n",resultlineori);
1.307 brouard 14749: nresult++; /* Sum of resultlines */
1.342 brouard 14750: /* printf("Result %d: result:%s\n",nresult, resultlineori); */
1.332 brouard 14751: /* removefirstspace(&resultlineori); */
14752:
14753: if(strstr(resultlineori,"v") !=0){
14754: printf("Error. 'v' must be in upper case 'V' result: %s ",resultlineori);
14755: fprintf(ficlog,"Error. 'v' must be in upper case result: %s ",resultlineori);fflush(ficlog);
14756: return 1;
14757: }
14758: trimbb(resultline, resultlineori); /* Suppressing double blank in the resultline */
1.342 brouard 14759: /* printf("Decoderesult resultline=\"%s\" resultlineori=\"%s\"\n", resultline, resultlineori); */
1.318 brouard 14760: if(nresult > MAXRESULTLINESPONE-1){
14761: printf("ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\nYou can use the 'r' parameter file '%s' which uses option mle=0 to get other results. ",MAXRESULTLINESPONE-1,nresult,rfileres);
14762: fprintf(ficlog,"ERROR: Current version of IMaCh limits the number of resultlines to %d, you used %d\nYou can use the 'r' parameter file '%s' which uses option mle=0 to get other results. ",MAXRESULTLINESPONE-1,nresult,rfileres);
1.307 brouard 14763: goto end;
14764: }
1.332 brouard 14765:
1.310 brouard 14766: if(!decoderesult(resultline, nresult)){ /* Fills TKresult[nresult] combination and Tresult[nresult][k4+1] combination values */
1.314 brouard 14767: fprintf(ficparo,"result: %s\n",resultline);
14768: fprintf(ficres,"result: %s\n",resultline);
14769: fprintf(ficlog,"result: %s\n",resultline);
1.310 brouard 14770: } else
14771: goto end;
1.307 brouard 14772: break;
14773: case 14:
14774: printf("Error: Unknown command '%s'\n",line);
14775: fprintf(ficlog,"Error: Unknown command '%s'\n",line);
1.314 brouard 14776: if(line[0] == ' ' || line[0] == '\n'){
14777: printf("It should not be an empty line '%s'\n",line);
14778: fprintf(ficlog,"It should not be an empty line '%s'\n",line);
14779: }
1.307 brouard 14780: if(ncovmodel >=2 && nresult==0 ){
14781: printf("ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
14782: fprintf(ficlog,"ERROR: no result lines! It should be at minimum 'result: V2=0 V1=1 or result:.' %s\n",line);
1.258 brouard 14783: }
1.307 brouard 14784: /* goto end; */
14785: break;
1.308 brouard 14786: case 15:
14787: printf("End of resultlines.\n");
14788: fprintf(ficlog,"End of resultlines.\n");
14789: break;
14790: default: /* parameterline =0 */
1.307 brouard 14791: nresult=1;
14792: decoderesult(".",nresult ); /* No covariate */
1.258 brouard 14793: } /* End switch parameterline */
14794: }while(endishere==0); /* End do */
1.126 brouard 14795:
1.230 brouard 14796: /* freqsummary(fileres, agemin, agemax, s, agev, nlstate, imx,Tvaraff,nbcode, ncodemax,mint,anint); */
1.145 brouard 14797: /* ,dateprev1,dateprev2,jprev1, mprev1,anprev1,jprev2, mprev2,anprev2); */
1.126 brouard 14798:
14799: replace_back_to_slash(pathc,pathcd); /* Even gnuplot wants a / */
1.194 brouard 14800: if(ageminpar == AGEOVERFLOW ||agemaxpar == -AGEOVERFLOW){
1.230 brouard 14801: printf("Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14802: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14803: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.230 brouard 14804: fprintf(ficlog,"Warning! Error in gnuplot file with ageminpar %f or agemaxpar %f overflow\n\
1.194 brouard 14805: This is probably because your parameter file doesn't \n contain the exact number of lines (or columns) corresponding to your model line.\n\
14806: Please run with mle=-1 to get a correct covariance matrix.\n",ageminpar,agemaxpar);
1.220 brouard 14807: }else{
1.270 brouard 14808: /* printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,fage, prevfcast, backcast, pathc,p, (int)anproj1-(int)agemin, (int)anback1-(int)agemax+1); */
1.296 brouard 14809: /* It seems that anprojd which is computed from the mean year at interview which is known yet because of freqsummary */
14810: /* date2dmy(dateintmean,&jintmean,&mintmean,&aintmean); */ /* Done in freqsummary */
14811: if(prvforecast==1){
14812: dateprojd=(jproj1+12*mproj1+365*anproj1)/365;
14813: jprojd=jproj1;
14814: mprojd=mproj1;
14815: anprojd=anproj1;
14816: dateprojf=(jproj2+12*mproj2+365*anproj2)/365;
14817: jprojf=jproj2;
14818: mprojf=mproj2;
14819: anprojf=anproj2;
14820: } else if(prvforecast == 2){
14821: dateprojd=dateintmean;
14822: date2dmy(dateprojd,&jprojd, &mprojd, &anprojd);
14823: dateprojf=dateintmean+yrfproj;
14824: date2dmy(dateprojf,&jprojf, &mprojf, &anprojf);
14825: }
14826: if(prvbackcast==1){
14827: datebackd=(jback1+12*mback1+365*anback1)/365;
14828: jbackd=jback1;
14829: mbackd=mback1;
14830: anbackd=anback1;
14831: datebackf=(jback2+12*mback2+365*anback2)/365;
14832: jbackf=jback2;
14833: mbackf=mback2;
14834: anbackf=anback2;
14835: } else if(prvbackcast == 2){
14836: datebackd=dateintmean;
14837: date2dmy(datebackd,&jbackd, &mbackd, &anbackd);
14838: datebackf=dateintmean-yrbproj;
14839: date2dmy(datebackf,&jbackf, &mbackf, &anbackf);
14840: }
14841:
1.350 brouard 14842: printinggnuplot(fileresu, optionfilefiname,ageminpar,agemaxpar,bage, fage, prevfcast, prevbcast, pathc,p, (int)anprojd-bage, (int)anbackd-fage);/* HERE valgrind Tvard*/
1.220 brouard 14843: }
14844: printinghtml(fileresu,title,datafile, firstpass, lastpass, stepm, weightopt, \
1.296 brouard 14845: model,imx,jmin,jmax,jmean,rfileres,popforecast,mobilav,prevfcast,mobilavproj,prevbcast, estepm, \
14846: jprev1,mprev1,anprev1,dateprev1, dateprojd, datebackd,jprev2,mprev2,anprev2,dateprev2,dateprojf, datebackf);
1.220 brouard 14847:
1.225 brouard 14848: /*------------ free_vector -------------*/
14849: /* chdir(path); */
1.220 brouard 14850:
1.215 brouard 14851: /* free_ivector(wav,1,imx); */ /* Moved after last prevalence call */
14852: /* free_imatrix(dh,1,lastpass-firstpass+2,1,imx); */
14853: /* free_imatrix(bh,1,lastpass-firstpass+2,1,imx); */
14854: /* free_imatrix(mw,1,lastpass-firstpass+2,1,imx); */
1.290 brouard 14855: free_lvector(num,firstobs,lastobs);
14856: free_vector(agedc,firstobs,lastobs);
1.126 brouard 14857: /*free_matrix(covar,0,NCOVMAX,1,n);*/
14858: /*free_matrix(covar,1,NCOVMAX,1,n);*/
14859: fclose(ficparo);
14860: fclose(ficres);
1.220 brouard 14861:
14862:
1.186 brouard 14863: /* Other results (useful)*/
1.220 brouard 14864:
14865:
1.126 brouard 14866: /*--------------- Prevalence limit (period or stable prevalence) --------------*/
1.180 brouard 14867: /*#include "prevlim.h"*/ /* Use ficrespl, ficlog */
14868: prlim=matrix(1,nlstate,1,nlstate);
1.332 brouard 14869: /* Computes the prevalence limit for each combination k of the dummy covariates by calling prevalim(k) */
1.209 brouard 14870: prevalence_limit(p, prlim, ageminpar, agemaxpar, ftolpl, &ncvyear);
1.126 brouard 14871: fclose(ficrespl);
14872:
14873: /*------------- h Pij x at various ages ------------*/
1.180 brouard 14874: /*#include "hpijx.h"*/
1.332 brouard 14875: /** h Pij x Probability to be in state j at age x+h being in i at x, for each combination k of dummies in the model line or to nres?*/
14876: /* calls hpxij with combination k */
1.180 brouard 14877: hPijx(p, bage, fage);
1.145 brouard 14878: fclose(ficrespij);
1.227 brouard 14879:
1.220 brouard 14880: /* ncovcombmax= pow(2,cptcoveff); */
1.332 brouard 14881: /*-------------- Variance of one-step probabilities for a combination ij or for nres ?---*/
1.145 brouard 14882: k=1;
1.126 brouard 14883: varprob(optionfilefiname, matcov, p, delti, nlstate, bage, fage,k,Tvar,nbcode, ncodemax,strstart);
1.227 brouard 14884:
1.269 brouard 14885: /* Prevalence for each covariate combination in probs[age][status][cov] */
14886: probs= ma3x(AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14887: for(i=AGEINF;i<=AGESUP;i++)
1.219 brouard 14888: for(j=1;j<=nlstate+ndeath;j++) /* ndeath is useless but a necessity to be compared with mobaverages */
1.225 brouard 14889: for(k=1;k<=ncovcombmax;k++)
14890: probs[i][j][k]=0.;
1.269 brouard 14891: prevalence(probs, ageminpar, agemaxpar, s, agev, nlstate, imx, Tvar, nbcode,
14892: ncodemax, mint, anint, dateprev1, dateprev2, firstpass, lastpass);
1.219 brouard 14893: if (mobilav!=0 ||mobilavproj !=0 ) {
1.269 brouard 14894: mobaverages= ma3x(AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
14895: for(i=AGEINF;i<=AGESUP;i++)
1.268 brouard 14896: for(j=1;j<=nlstate+ndeath;j++)
1.227 brouard 14897: for(k=1;k<=ncovcombmax;k++)
14898: mobaverages[i][j][k]=0.;
1.219 brouard 14899: mobaverage=mobaverages;
14900: if (mobilav!=0) {
1.235 brouard 14901: printf("Movingaveraging observed prevalence\n");
1.258 brouard 14902: fprintf(ficlog,"Movingaveraging observed prevalence\n");
1.227 brouard 14903: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilav)!=0){
14904: fprintf(ficlog," Error in movingaverage mobilav=%d\n",mobilav);
14905: printf(" Error in movingaverage mobilav=%d\n",mobilav);
14906: }
1.269 brouard 14907: } else if (mobilavproj !=0) {
1.235 brouard 14908: printf("Movingaveraging projected observed prevalence\n");
1.258 brouard 14909: fprintf(ficlog,"Movingaveraging projected observed prevalence\n");
1.227 brouard 14910: if (movingaverage(probs, ageminpar, agemaxpar, mobaverage, mobilavproj)!=0){
14911: fprintf(ficlog," Error in movingaverage mobilavproj=%d\n",mobilavproj);
14912: printf(" Error in movingaverage mobilavproj=%d\n",mobilavproj);
14913: }
1.269 brouard 14914: }else{
14915: printf("Internal error moving average\n");
14916: fflush(stdout);
14917: exit(1);
1.219 brouard 14918: }
14919: }/* end if moving average */
1.227 brouard 14920:
1.126 brouard 14921: /*---------- Forecasting ------------------*/
1.296 brouard 14922: if(prevfcast==1){
14923: /* /\* if(stepm ==1){*\/ */
14924: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14925: /*This done previously after freqsummary.*/
14926: /* dateprojd=(jproj1+12*mproj1+365*anproj1)/365; */
14927: /* dateprojf=(jproj2+12*mproj2+365*anproj2)/365; */
14928:
14929: /* } else if (prvforecast==2){ */
14930: /* /\* if(stepm ==1){*\/ */
14931: /* /\* anproj1, mproj1, jproj1 either read explicitly or yrfproj *\/ */
14932: /* } */
14933: /*prevforecast(fileresu, dateintmean, anproj1, mproj1, jproj1, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, anproj2, p, cptcoveff);*/
14934: prevforecast(fileresu,dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2, mobilavproj, mobaverage, bage, fage, firstpass, lastpass, p, cptcoveff);
1.126 brouard 14935: }
1.269 brouard 14936:
1.296 brouard 14937: /* Prevbcasting */
14938: if(prevbcast==1){
1.219 brouard 14939: ddnewms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14940: ddoldms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14941: ddsavms=matrix(1,nlstate+ndeath,1,nlstate+ndeath);
14942:
14943: /*--------------- Back Prevalence limit (period or stable prevalence) --------------*/
14944:
14945: bprlim=matrix(1,nlstate,1,nlstate);
1.269 brouard 14946:
1.219 brouard 14947: back_prevalence_limit(p, bprlim, ageminpar, agemaxpar, ftolpl, &ncvyear, dateprev1, dateprev2, firstpass, lastpass, mobilavproj);
14948: fclose(ficresplb);
14949:
1.222 brouard 14950: hBijx(p, bage, fage, mobaverage);
14951: fclose(ficrespijb);
1.219 brouard 14952:
1.296 brouard 14953: /* /\* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, *\/ */
14954: /* /\* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); *\/ */
14955: /* prevbackforecast(fileresu, mobaverage, anback1, mback1, jback1, agemin, agemax, dateprev1, dateprev2, */
14956: /* mobilavproj, bage, fage, firstpass, lastpass, anback2, p, cptcoveff); */
14957: prevbackforecast(fileresu, mobaverage, dateintmean, dateprojd, dateprojf, agemin, agemax, dateprev1, dateprev2,
14958: mobilavproj, bage, fage, firstpass, lastpass, p, cptcoveff);
14959:
14960:
1.269 brouard 14961: varbprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, bprlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 14962:
14963:
1.269 brouard 14964: free_matrix(bprlim,1,nlstate,1,nlstate); /*here or after loop ? */
1.219 brouard 14965: free_matrix(ddnewms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14966: free_matrix(ddsavms, 1, nlstate+ndeath, 1, nlstate+ndeath);
14967: free_matrix(ddoldms, 1, nlstate+ndeath, 1, nlstate+ndeath);
1.296 brouard 14968: } /* end Prevbcasting */
1.268 brouard 14969:
1.186 brouard 14970:
14971: /* ------ Other prevalence ratios------------ */
1.126 brouard 14972:
1.215 brouard 14973: free_ivector(wav,1,imx);
14974: free_imatrix(dh,1,lastpass-firstpass+2,1,imx);
14975: free_imatrix(bh,1,lastpass-firstpass+2,1,imx);
14976: free_imatrix(mw,1,lastpass-firstpass+2,1,imx);
1.218 brouard 14977:
14978:
1.127 brouard 14979: /*---------- Health expectancies, no variances ------------*/
1.218 brouard 14980:
1.201 brouard 14981: strcpy(filerese,"E_");
14982: strcat(filerese,fileresu);
1.126 brouard 14983: if((ficreseij=fopen(filerese,"w"))==NULL) {
14984: printf("Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14985: fprintf(ficlog,"Problem with Health Exp. resultfile: %s\n", filerese); exit(0);
14986: }
1.208 brouard 14987: printf("Computing Health Expectancies: result on file '%s' ...", filerese);fflush(stdout);
14988: fprintf(ficlog,"Computing Health Expectancies: result on file '%s' ...", filerese);fflush(ficlog);
1.238 brouard 14989:
14990: pstamp(ficreseij);
1.219 brouard 14991:
1.351 brouard 14992: /* i1=pow(2,cptcoveff); /\* Number of combination of dummy covariates *\/ */
14993: /* if (cptcovn < 1){i1=1;} */
1.235 brouard 14994:
1.351 brouard 14995: for(nres=1; nres <= nresult; nres++){ /* For each resultline */
14996: /* for(k=1; k<=i1;k++){ /\* For any combination of dummy covariates, fixed and varying *\/ */
14997: /* if(i1 != 1 && TKresult[nres]!= k) */
14998: /* continue; */
1.219 brouard 14999: fprintf(ficreseij,"\n#****** ");
1.235 brouard 15000: printf("\n#****** ");
1.351 brouard 15001: for(j=1;j<=cptcovs;j++){
15002: /* for(j=1;j<=cptcoveff;j++) { */
15003: /* fprintf(ficreseij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15004: fprintf(ficreseij," V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
15005: printf(" V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]);
15006: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
1.235 brouard 15007: }
15008: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.337 brouard 15009: printf(" V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]); /* TvarsQ[j] gives the name of the jth quantitative (fixed or time v) */
15010: fprintf(ficreseij,"V%d=%lg ",TvarsQ[j], TinvDoQresult[nres][TvarsQ[j]]);
1.219 brouard 15011: }
15012: fprintf(ficreseij,"******\n");
1.235 brouard 15013: printf("******\n");
1.219 brouard 15014:
15015: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15016: oldm=oldms;savm=savms;
1.330 brouard 15017: /* printf("HELLO Entering evsij bage=%d fage=%d k=%d estepm=%d nres=%d\n",(int) bage, (int)fage, k, estepm, nres); */
1.235 brouard 15018: evsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, strstart, nres);
1.127 brouard 15019:
1.219 brouard 15020: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.127 brouard 15021: }
15022: fclose(ficreseij);
1.208 brouard 15023: printf("done evsij\n");fflush(stdout);
15024: fprintf(ficlog,"done evsij\n");fflush(ficlog);
1.269 brouard 15025:
1.218 brouard 15026:
1.227 brouard 15027: /*---------- State-specific expectancies and variances ------------*/
1.336 brouard 15028: /* Should be moved in a function */
1.201 brouard 15029: strcpy(filerest,"T_");
15030: strcat(filerest,fileresu);
1.127 brouard 15031: if((ficrest=fopen(filerest,"w"))==NULL) {
15032: printf("Problem with total LE resultfile: %s\n", filerest);goto end;
15033: fprintf(ficlog,"Problem with total LE resultfile: %s\n", filerest);goto end;
15034: }
1.208 brouard 15035: printf("Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(stdout);
15036: fprintf(ficlog,"Computing Total Life expectancies with their standard errors: file '%s' ...\n", filerest); fflush(ficlog);
1.201 brouard 15037: strcpy(fileresstde,"STDE_");
15038: strcat(fileresstde,fileresu);
1.126 brouard 15039: if((ficresstdeij=fopen(fileresstde,"w"))==NULL) {
1.227 brouard 15040: printf("Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
15041: fprintf(ficlog,"Problem with State specific Exp. and std errors resultfile: %s\n", fileresstde); exit(0);
1.126 brouard 15042: }
1.227 brouard 15043: printf(" Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
15044: fprintf(ficlog," Computing State-specific Expectancies and standard errors: result on file '%s' \n", fileresstde);
1.126 brouard 15045:
1.201 brouard 15046: strcpy(filerescve,"CVE_");
15047: strcat(filerescve,fileresu);
1.126 brouard 15048: if((ficrescveij=fopen(filerescve,"w"))==NULL) {
1.227 brouard 15049: printf("Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
15050: fprintf(ficlog,"Problem with Covar. State-specific Exp. resultfile: %s\n", filerescve); exit(0);
1.126 brouard 15051: }
1.227 brouard 15052: printf(" Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
15053: fprintf(ficlog," Computing Covar. of State-specific Expectancies: result on file '%s' \n", filerescve);
1.126 brouard 15054:
1.201 brouard 15055: strcpy(fileresv,"V_");
15056: strcat(fileresv,fileresu);
1.126 brouard 15057: if((ficresvij=fopen(fileresv,"w"))==NULL) {
15058: printf("Problem with variance resultfile: %s\n", fileresv);exit(0);
15059: fprintf(ficlog,"Problem with variance resultfile: %s\n", fileresv);exit(0);
15060: }
1.227 brouard 15061: printf(" Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(stdout);
15062: fprintf(ficlog," Computing Variance-covariance of State-specific Expectancies: file '%s' ... ", fileresv);fflush(ficlog);
1.126 brouard 15063:
1.235 brouard 15064: i1=pow(2,cptcoveff); /* Number of combination of dummy covariates */
15065: if (cptcovn < 1){i1=1;}
15066:
1.334 brouard 15067: for(nres=1; nres <= nresult; nres++) /* For each resultline, find the combination and output results according to the values of dummies and then quanti. */
15068: for(k=1; k<=i1;k++){ /* For any combination of dummy covariates, fixed and varying. For each nres and each value at position k
15069: * we know Tresult[nres][result_position]= value of the dummy variable at the result_position in the nres resultline
15070: * Tvqresult[nres][result_position]= id of the variable at the result_position in the nres resultline
15071: * and Tqresult[nres][result_position]= value of the variable at the result_position in the nres resultline */
15072: /* */
15073: if(i1 != 1 && TKresult[nres]!= k) /* TKresult[nres] is the combination of this nres resultline. All the i1 combinations are not output */
1.235 brouard 15074: continue;
1.350 brouard 15075: printf("\n# model %s \n#****** Result for:", model); /* HERE model is empty */
1.321 brouard 15076: fprintf(ficrest,"\n# model %s \n#****** Result for:", model);
15077: fprintf(ficlog,"\n# model %s \n#****** Result for:", model);
1.334 brouard 15078: /* It might not be a good idea to mix dummies and quantitative */
15079: /* for(j=1;j<=cptcoveff;j++){ /\* j=resultpos. Could be a loop on cptcovs: number of single dummy covariate in the result line as well as in the model *\/ */
15080: for(j=1;j<=cptcovs;j++){ /* j=resultpos. Could be a loop on cptcovs: number of single covariate (dummy or quantitative) in the result line as well as in the model */
15081: /* printf("V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); /\* Output by variables in the resultline *\/ */
15082: /* Tvaraff[j] is the name of the dummy variable in position j in the equation model:
15083: * Tvaraff[1]@9={4, 3, 0, 0, 0, 0, 0, 0, 0}, in model=V5+V4+V3+V4*V3+V5*age
15084: * (V5 is quanti) V4 and V3 are dummies
15085: * TnsdVar[4] is the position 1 and TnsdVar[3]=2 in codtabm(k,l)(V4 V3)=V4 V3
15086: * l=1 l=2
15087: * k=1 1 1 0 0
15088: * k=2 2 1 1 0
15089: * k=3 [1] [2] 0 1
15090: * k=4 2 2 1 1
15091: * If nres=1 result: V3=1 V4=0 then k=3 and outputs
15092: * If nres=2 result: V4=1 V3=0 then k=2 and outputs
15093: * nres=1 =>k=3 j=1 V4= nbcode[4][codtabm(3,1)=1)=0; j=2 V3= nbcode[3][codtabm(3,2)=2]=1
15094: * nres=2 =>k=2 j=1 V4= nbcode[4][codtabm(2,1)=2)=1; j=2 V3= nbcode[3][codtabm(2,2)=1]=0
15095: */
15096: /* Tvresult[nres][j] Name of the variable at position j in this resultline */
15097: /* Tresult[nres][j] Value of this variable at position j could be a float if quantitative */
15098: /* We give up with the combinations!! */
1.342 brouard 15099: /* if(debugILK) */
15100: /* printf("\n j=%d In computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d Fixed[modelresult[nres][j]]=%d\n", j, nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff,Fixed[modelresult[nres][j]]); /\* end if dummy or quanti *\/ */
1.334 brouard 15101:
15102: if(Dummy[modelresult[nres][j]]==0){/* Dummy variable of the variable in position modelresult in the model corresponding to j in resultline */
1.344 brouard 15103: /* printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][j]); /\* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline *\/ */ /* TinvDoQresult[nres][Name of the variable] */
15104: printf("V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); /* Output of each value for the combination TKresult[nres], ordered by the covariate values in the resultline */
15105: fprintf(ficlog,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
15106: fprintf(ficrest,"V%d=%lg ",Tvresult[nres][j],TinvDoQresult[nres][Tvresult[nres][j]]); /* Output of each value for the combination TKresult[nres], ordere by the covariate values in the resultline */
1.334 brouard 15107: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15108: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15109: }else{
15110: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15111: }
15112: /* fprintf(ficrest,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15113: /* fprintf(ficlog,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15114: }else if(Dummy[modelresult[nres][j]]==1){ /* Quanti variable */
15115: /* For each selected (single) quantitative value */
1.337 brouard 15116: printf(" V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15117: fprintf(ficlog," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
15118: fprintf(ficrest," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][j]);
1.334 brouard 15119: if(Fixed[modelresult[nres][j]]==0){ /* Fixed */
15120: printf("fixed ");fprintf(ficlog,"fixed ");fprintf(ficrest,"fixed ");
15121: }else{
15122: printf("varyi ");fprintf(ficlog,"varyi ");fprintf(ficrest,"varyi ");
15123: }
15124: }else{
15125: printf("Error in computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d \n", nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff); /* end if dummy or quanti */
15126: fprintf(ficlog,"Error in computing T_ Dummy[modelresult[%d][%d]]=%d, modelresult[%d][%d]=%d cptcovs=%d, cptcoveff=%d \n", nres, j, Dummy[modelresult[nres][j]],nres,j,modelresult[nres][j],cptcovs, cptcoveff); /* end if dummy or quanti */
15127: exit(1);
15128: }
1.335 brouard 15129: } /* End loop for each variable in the resultline */
1.334 brouard 15130: /* for (j=1; j<= nsq; j++){ /\* For each selected (single) quantitative value *\/ */
15131: /* printf(" V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /\* Wrong j is not in the equation model *\/ */
15132: /* fprintf(ficrest," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15133: /* fprintf(ficlog," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); */
15134: /* } */
1.208 brouard 15135: fprintf(ficrest,"******\n");
1.227 brouard 15136: fprintf(ficlog,"******\n");
15137: printf("******\n");
1.208 brouard 15138:
15139: fprintf(ficresstdeij,"\n#****** ");
15140: fprintf(ficrescveij,"\n#****** ");
1.337 brouard 15141: /* It could have been: for(j=1;j<=cptcoveff;j++) {printf("V=%d=%lg",Tvresult[nres][cpt],TinvDoQresult[nres][Tvresult[nres][cpt]]);} */
15142: /* But it won't be sorted and depends on how the resultline is ordered */
1.225 brouard 15143: for(j=1;j<=cptcoveff;j++) {
1.334 brouard 15144: fprintf(ficresstdeij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15145: /* fprintf(ficresstdeij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15146: /* fprintf(ficrescveij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[Tvaraff[j]])]); */
15147: }
15148: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value, TvarsQind gives the position of a quantitative in model equation */
1.337 brouard 15149: fprintf(ficresstdeij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
15150: fprintf(ficrescveij," V%d=%lg ",Tvar[TvarsQind[j]],Tqresult[nres][resultmodel[nres][TvarsQind[j]]]);
1.235 brouard 15151: }
1.208 brouard 15152: fprintf(ficresstdeij,"******\n");
15153: fprintf(ficrescveij,"******\n");
15154:
15155: fprintf(ficresvij,"\n#****** ");
1.238 brouard 15156: /* pstamp(ficresvij); */
1.225 brouard 15157: for(j=1;j<=cptcoveff;j++)
1.335 brouard 15158: fprintf(ficresvij,"V%d=%d ",Tvresult[nres][j],Tresult[nres][j]);
15159: /* fprintf(ficresvij,"V%d=%d ",Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,TnsdVar[TnsdVar[Tvaraff[j]]])]); */
1.235 brouard 15160: for (j=1; j<= nsq; j++){ /* For each selected (single) quantitative value */
1.332 brouard 15161: /* fprintf(ficresvij," V%d=%f ",Tvqresult[nres][j],Tqresult[nres][j]); /\* To solve *\/ */
1.337 brouard 15162: fprintf(ficresvij," V%d=%lg ",Tvqresult[nres][j],Tqresult[nres][resultmodel[nres][j]]); /* Solved */
1.235 brouard 15163: }
1.208 brouard 15164: fprintf(ficresvij,"******\n");
15165:
15166: eij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15167: oldm=oldms;savm=savms;
1.235 brouard 15168: printf(" cvevsij ");
15169: fprintf(ficlog, " cvevsij ");
15170: cvevsij(eij, p, nlstate, stepm, (int) bage, (int)fage, oldm, savm, k, estepm, delti, matcov, strstart, nres);
1.208 brouard 15171: printf(" end cvevsij \n ");
15172: fprintf(ficlog, " end cvevsij \n ");
15173:
15174: /*
15175: */
15176: /* goto endfree; */
15177:
15178: vareij=ma3x(1,nlstate,1,nlstate,(int) bage, (int) fage);
15179: pstamp(ficrest);
15180:
1.269 brouard 15181: epj=vector(1,nlstate+1);
1.208 brouard 15182: for(vpopbased=0; vpopbased <= popbased; vpopbased++){ /* Done for vpopbased=0 and vpopbased=1 if popbased==1*/
1.227 brouard 15183: oldm=oldms;savm=savms; /* ZZ Segmentation fault */
15184: cptcod= 0; /* To be deleted */
15185: printf("varevsij vpopbased=%d \n",vpopbased);
15186: fprintf(ficlog, "varevsij vpopbased=%d \n",vpopbased);
1.235 brouard 15187: varevsij(optionfilefiname, vareij, matcov, p, delti, nlstate, stepm, (int) bage, (int) fage, oldm, savm, prlim, ftolpl, &ncvyear, k, estepm, cptcov,cptcod,vpopbased,mobilav, strstart, nres); /* cptcod not initialized Intel */
1.227 brouard 15188: fprintf(ficrest,"# Total life expectancy with std error and decomposition into time to be expected in each health state\n# (weighted average of eij where weights are ");
15189: if(vpopbased==1)
15190: fprintf(ficrest,"the age specific prevalence observed (cross-sectionally) in the population i.e cross-sectionally\n in each health state (popbased=1) (mobilav=%d)\n",mobilav);
15191: else
1.288 brouard 15192: fprintf(ficrest,"the age specific forward period (stable) prevalences in each health state \n");
1.335 brouard 15193: fprintf(ficrest,"# Age popbased mobilav e.. (std) "); /* Adding covariate values? */
1.227 brouard 15194: for (i=1;i<=nlstate;i++) fprintf(ficrest,"e.%d (std) ",i);
15195: fprintf(ficrest,"\n");
15196: /* printf("Which p?\n"); for(i=1;i<=npar;i++)printf("p[i=%d]=%lf,",i,p[i]);printf("\n"); */
1.288 brouard 15197: printf("Computing age specific forward period (stable) prevalences in each health state \n");
15198: fprintf(ficlog,"Computing age specific forward period (stable) prevalences in each health state \n");
1.227 brouard 15199: for(age=bage; age <=fage ;age++){
1.235 brouard 15200: prevalim(prlim, nlstate, p, age, oldm, savm, ftolpl, &ncvyear, k, nres); /*ZZ Is it the correct prevalim */
1.227 brouard 15201: if (vpopbased==1) {
15202: if(mobilav ==0){
15203: for(i=1; i<=nlstate;i++)
15204: prlim[i][i]=probs[(int)age][i][k];
15205: }else{ /* mobilav */
15206: for(i=1; i<=nlstate;i++)
15207: prlim[i][i]=mobaverage[(int)age][i][k];
15208: }
15209: }
1.219 brouard 15210:
1.227 brouard 15211: fprintf(ficrest," %4.0f %d %d",age, vpopbased, mobilav);
15212: /* fprintf(ficrest," %4.0f %d %d %d %d",age, vpopbased, mobilav,Tvaraff[j],nbcode[Tvaraff[j]][codtabm(k,j)]); */ /* to be done */
15213: /* printf(" age %4.0f ",age); */
15214: for(j=1, epj[nlstate+1]=0.;j <=nlstate;j++){
15215: for(i=1, epj[j]=0.;i <=nlstate;i++) {
15216: epj[j] += prlim[i][i]*eij[i][j][(int)age];
15217: /*ZZZ printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]);*/
15218: /* printf("%lf %lf ", prlim[i][i] ,eij[i][j][(int)age]); */
15219: }
15220: epj[nlstate+1] +=epj[j];
15221: }
15222: /* printf(" age %4.0f \n",age); */
1.219 brouard 15223:
1.227 brouard 15224: for(i=1, vepp=0.;i <=nlstate;i++)
15225: for(j=1;j <=nlstate;j++)
15226: vepp += vareij[i][j][(int)age];
15227: fprintf(ficrest," %7.3f (%7.3f)", epj[nlstate+1],sqrt(vepp));
15228: for(j=1;j <=nlstate;j++){
15229: fprintf(ficrest," %7.3f (%7.3f)", epj[j],sqrt(vareij[j][j][(int)age]));
15230: }
15231: fprintf(ficrest,"\n");
15232: }
1.208 brouard 15233: } /* End vpopbased */
1.269 brouard 15234: free_vector(epj,1,nlstate+1);
1.208 brouard 15235: free_ma3x(eij,1,nlstate,1,nlstate,(int) bage, (int)fage);
15236: free_ma3x(vareij,1,nlstate,1,nlstate,(int) bage, (int)fage);
1.235 brouard 15237: printf("done selection\n");fflush(stdout);
15238: fprintf(ficlog,"done selection\n");fflush(ficlog);
1.208 brouard 15239:
1.335 brouard 15240: } /* End k selection or end covariate selection for nres */
1.227 brouard 15241:
15242: printf("done State-specific expectancies\n");fflush(stdout);
15243: fprintf(ficlog,"done State-specific expectancies\n");fflush(ficlog);
15244:
1.335 brouard 15245: /* variance-covariance of forward period prevalence */
1.269 brouard 15246: varprlim(fileresu, nresult, mobaverage, mobilavproj, bage, fage, prlim, &ncvyear, ftolpl, p, matcov, delti, stepm, cptcoveff);
1.268 brouard 15247:
1.227 brouard 15248:
1.290 brouard 15249: free_vector(weight,firstobs,lastobs);
1.351 brouard 15250: free_imatrix(Tvardk,0,NCOVMAX,1,2);
1.227 brouard 15251: free_imatrix(Tvard,1,NCOVMAX,1,2);
1.290 brouard 15252: free_imatrix(s,1,maxwav+1,firstobs,lastobs);
15253: free_matrix(anint,1,maxwav,firstobs,lastobs);
15254: free_matrix(mint,1,maxwav,firstobs,lastobs);
15255: free_ivector(cod,firstobs,lastobs);
1.227 brouard 15256: free_ivector(tab,1,NCOVMAX);
15257: fclose(ficresstdeij);
15258: fclose(ficrescveij);
15259: fclose(ficresvij);
15260: fclose(ficrest);
15261: fclose(ficpar);
15262:
15263:
1.126 brouard 15264: /*---------- End : free ----------------*/
1.219 brouard 15265: if (mobilav!=0 ||mobilavproj !=0)
1.269 brouard 15266: free_ma3x(mobaverages,AGEINF, AGESUP,1,nlstate+ndeath, 1,ncovcombmax); /* We need to have a squared matrix with prevalence of the dead! */
15267: free_ma3x(probs,AGEINF,AGESUP,1,nlstate+ndeath, 1,ncovcombmax);
1.220 brouard 15268: free_matrix(prlim,1,nlstate,1,nlstate); /*here or after loop ? */
15269: free_matrix(pmmij,1,nlstate+ndeath,1,nlstate+ndeath);
1.126 brouard 15270: } /* mle==-3 arrives here for freeing */
1.227 brouard 15271: /* endfree:*/
15272: free_matrix(oldms, 1,nlstate+ndeath,1,nlstate+ndeath);
15273: free_matrix(newms, 1,nlstate+ndeath,1,nlstate+ndeath);
15274: free_matrix(savms, 1,nlstate+ndeath,1,nlstate+ndeath);
1.341 brouard 15275: /* if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,1,ntv+nqtv,firstobs,lastobs); */
15276: if(ntv+nqtv>=1)free_ma3x(cotvar,1,maxwav,ncovcol+nqv+1,ncovcol+nqv+ntv+nqtv,firstobs,lastobs);
1.290 brouard 15277: if(nqtv>=1)free_ma3x(cotqvar,1,maxwav,1,nqtv,firstobs,lastobs);
15278: if(nqv>=1)free_matrix(coqvar,1,nqv,firstobs,lastobs);
15279: free_matrix(covar,0,NCOVMAX,firstobs,lastobs);
1.227 brouard 15280: free_matrix(matcov,1,npar,1,npar);
15281: free_matrix(hess,1,npar,1,npar);
15282: /*free_vector(delti,1,npar);*/
15283: free_ma3x(delti3,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15284: free_matrix(agev,1,maxwav,1,imx);
1.269 brouard 15285: free_ma3x(paramstart,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
1.227 brouard 15286: free_ma3x(param,1,nlstate,1, nlstate+ndeath-1,1,ncovmodel);
15287:
15288: free_ivector(ncodemax,1,NCOVMAX);
15289: free_ivector(ncodemaxwundef,1,NCOVMAX);
15290: free_ivector(Dummy,-1,NCOVMAX);
15291: free_ivector(Fixed,-1,NCOVMAX);
1.349 brouard 15292: free_ivector(DummyV,-1,NCOVMAX);
15293: free_ivector(FixedV,-1,NCOVMAX);
1.227 brouard 15294: free_ivector(Typevar,-1,NCOVMAX);
15295: free_ivector(Tvar,1,NCOVMAX);
1.234 brouard 15296: free_ivector(TvarsQ,1,NCOVMAX);
15297: free_ivector(TvarsQind,1,NCOVMAX);
15298: free_ivector(TvarsD,1,NCOVMAX);
1.330 brouard 15299: free_ivector(TnsdVar,1,NCOVMAX);
1.234 brouard 15300: free_ivector(TvarsDind,1,NCOVMAX);
1.231 brouard 15301: free_ivector(TvarFD,1,NCOVMAX);
15302: free_ivector(TvarFDind,1,NCOVMAX);
1.232 brouard 15303: free_ivector(TvarF,1,NCOVMAX);
15304: free_ivector(TvarFind,1,NCOVMAX);
15305: free_ivector(TvarV,1,NCOVMAX);
15306: free_ivector(TvarVind,1,NCOVMAX);
15307: free_ivector(TvarA,1,NCOVMAX);
15308: free_ivector(TvarAind,1,NCOVMAX);
1.231 brouard 15309: free_ivector(TvarFQ,1,NCOVMAX);
15310: free_ivector(TvarFQind,1,NCOVMAX);
15311: free_ivector(TvarVD,1,NCOVMAX);
15312: free_ivector(TvarVDind,1,NCOVMAX);
15313: free_ivector(TvarVQ,1,NCOVMAX);
15314: free_ivector(TvarVQind,1,NCOVMAX);
1.349 brouard 15315: free_ivector(TvarAVVA,1,NCOVMAX);
15316: free_ivector(TvarAVVAind,1,NCOVMAX);
15317: free_ivector(TvarVVA,1,NCOVMAX);
15318: free_ivector(TvarVVAind,1,NCOVMAX);
1.339 brouard 15319: free_ivector(TvarVV,1,NCOVMAX);
15320: free_ivector(TvarVVind,1,NCOVMAX);
15321:
1.230 brouard 15322: free_ivector(Tvarsel,1,NCOVMAX);
15323: free_vector(Tvalsel,1,NCOVMAX);
1.227 brouard 15324: free_ivector(Tposprod,1,NCOVMAX);
15325: free_ivector(Tprod,1,NCOVMAX);
15326: free_ivector(Tvaraff,1,NCOVMAX);
1.338 brouard 15327: free_ivector(invalidvarcomb,0,ncovcombmax);
1.227 brouard 15328: free_ivector(Tage,1,NCOVMAX);
15329: free_ivector(Tmodelind,1,NCOVMAX);
1.228 brouard 15330: free_ivector(TmodelInvind,1,NCOVMAX);
15331: free_ivector(TmodelInvQind,1,NCOVMAX);
1.332 brouard 15332:
15333: free_matrix(precov, 1,MAXRESULTLINESPONE,1,NCOVMAX+1); /* Could be elsewhere ?*/
15334:
1.227 brouard 15335: free_imatrix(nbcode,0,NCOVMAX,0,NCOVMAX);
15336: /* free_imatrix(codtab,1,100,1,10); */
1.126 brouard 15337: fflush(fichtm);
15338: fflush(ficgp);
15339:
1.227 brouard 15340:
1.126 brouard 15341: if((nberr >0) || (nbwarn>0)){
1.216 brouard 15342: printf("End of Imach with %d errors and/or %d warnings. Please look at the log file for details.\n",nberr,nbwarn);
15343: fprintf(ficlog,"End of Imach with %d errors and/or warnings %d. Please look at the log file for details.\n",nberr,nbwarn);
1.126 brouard 15344: }else{
15345: printf("End of Imach\n");
15346: fprintf(ficlog,"End of Imach\n");
15347: }
15348: printf("See log file on %s\n",filelog);
15349: /* gettimeofday(&end_time, (struct timezone*)0);*/ /* after time */
1.157 brouard 15350: /*(void) gettimeofday(&end_time,&tzp);*/
15351: rend_time = time(NULL);
15352: end_time = *localtime(&rend_time);
15353: /* tml = *localtime(&end_time.tm_sec); */
15354: strcpy(strtend,asctime(&end_time));
1.126 brouard 15355: printf("Local time at start %s\nLocal time at end %s",strstart, strtend);
15356: fprintf(ficlog,"Local time at start %s\nLocal time at end %s\n",strstart, strtend);
1.157 brouard 15357: printf("Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
1.227 brouard 15358:
1.157 brouard 15359: printf("Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
15360: fprintf(ficlog,"Total time used %s\n", asc_diff_time(rend_time -rstart_time,tmpout));
15361: fprintf(ficlog,"Total time was %.0lf Sec.\n", difftime(rend_time,rstart_time));
1.126 brouard 15362: /* printf("Total time was %d uSec.\n", total_usecs);*/
15363: /* if(fileappend(fichtm,optionfilehtm)){ */
15364: fprintf(fichtm,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15365: fclose(fichtm);
15366: fprintf(fichtmcov,"<br>Local time at start %s<br>Local time at end %s<br>\n</body></html>",strstart, strtend);
15367: fclose(fichtmcov);
15368: fclose(ficgp);
15369: fclose(ficlog);
15370: /*------ End -----------*/
1.227 brouard 15371:
1.281 brouard 15372:
15373: /* Executes gnuplot */
1.227 brouard 15374:
15375: printf("Before Current directory %s!\n",pathcd);
1.184 brouard 15376: #ifdef WIN32
1.227 brouard 15377: if (_chdir(pathcd) != 0)
15378: printf("Can't move to directory %s!\n",path);
15379: if(_getcwd(pathcd,MAXLINE) > 0)
1.184 brouard 15380: #else
1.227 brouard 15381: if(chdir(pathcd) != 0)
15382: printf("Can't move to directory %s!\n", path);
15383: if (getcwd(pathcd, MAXLINE) > 0)
1.184 brouard 15384: #endif
1.126 brouard 15385: printf("Current directory %s!\n",pathcd);
15386: /*strcat(plotcmd,CHARSEPARATOR);*/
15387: sprintf(plotcmd,"gnuplot");
1.157 brouard 15388: #ifdef _WIN32
1.126 brouard 15389: sprintf(plotcmd,"\"%sgnuplot.exe\"",pathimach);
15390: #endif
15391: if(!stat(plotcmd,&info)){
1.158 brouard 15392: printf("Error or gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15393: if(!stat(getenv("GNUPLOTBIN"),&info)){
1.158 brouard 15394: printf("Error or gnuplot program not found: '%s' Environment GNUPLOTBIN not set.\n",plotcmd);fflush(stdout);
1.126 brouard 15395: }else
15396: strcpy(pplotcmd,plotcmd);
1.157 brouard 15397: #ifdef __unix
1.126 brouard 15398: strcpy(plotcmd,GNUPLOTPROGRAM);
15399: if(!stat(plotcmd,&info)){
1.158 brouard 15400: printf("Error gnuplot program not found: '%s'\n",plotcmd);fflush(stdout);
1.126 brouard 15401: }else
15402: strcpy(pplotcmd,plotcmd);
15403: #endif
15404: }else
15405: strcpy(pplotcmd,plotcmd);
15406:
15407: sprintf(plotcmd,"%s %s",pplotcmd, optionfilegnuplot);
1.158 brouard 15408: printf("Starting graphs with: '%s'\n",plotcmd);fflush(stdout);
1.292 brouard 15409: strcpy(pplotcmd,plotcmd);
1.227 brouard 15410:
1.126 brouard 15411: if((outcmd=system(plotcmd)) != 0){
1.292 brouard 15412: printf("Error in gnuplot, command might not be in your path: '%s', err=%d\n", plotcmd, outcmd);
1.154 brouard 15413: printf("\n Trying if gnuplot resides on the same directory that IMaCh\n");
1.152 brouard 15414: sprintf(plotcmd,"%sgnuplot %s", pathimach, optionfilegnuplot);
1.292 brouard 15415: if((outcmd=system(plotcmd)) != 0){
1.153 brouard 15416: printf("\n Still a problem with gnuplot command %s, err=%d\n", plotcmd, outcmd);
1.292 brouard 15417: strcpy(plotcmd,pplotcmd);
15418: }
1.126 brouard 15419: }
1.158 brouard 15420: printf(" Successful, please wait...");
1.126 brouard 15421: while (z[0] != 'q') {
15422: /* chdir(path); */
1.154 brouard 15423: printf("\nType e to edit results with your browser, g to graph again and q for exit: ");
1.126 brouard 15424: scanf("%s",z);
15425: /* if (z[0] == 'c') system("./imach"); */
15426: if (z[0] == 'e') {
1.158 brouard 15427: #ifdef __APPLE__
1.152 brouard 15428: sprintf(pplotcmd, "open %s", optionfilehtm);
1.157 brouard 15429: #elif __linux
15430: sprintf(pplotcmd, "xdg-open %s", optionfilehtm);
1.153 brouard 15431: #else
1.152 brouard 15432: sprintf(pplotcmd, "%s", optionfilehtm);
1.153 brouard 15433: #endif
15434: printf("Starting browser with: %s",pplotcmd);fflush(stdout);
15435: system(pplotcmd);
1.126 brouard 15436: }
15437: else if (z[0] == 'g') system(plotcmd);
15438: else if (z[0] == 'q') exit(0);
15439: }
1.227 brouard 15440: end:
1.126 brouard 15441: while (z[0] != 'q') {
1.195 brouard 15442: printf("\nType q for exiting: "); fflush(stdout);
1.126 brouard 15443: scanf("%s",z);
15444: }
1.283 brouard 15445: printf("End\n");
1.282 brouard 15446: exit(0);
1.126 brouard 15447: }
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